Normalized nesting cube and mapping system for machine learning to color coordinate products, patterns and objects on a homogenized ecommerce platform

ABSTRACT

A computer-implemented method for normalizing a RGB (red, green, blue) digital color space into a universal digital color standard. The RGB digital color space is mapped into a three-dimensional color cube. The sides of the three-dimensional color cube get progressively smaller until the sides converge in a center point of the three-dimensional color cube to form a three-dimensional color nesting cube. Duplicate colors in the RGB digital color space that are not distinguishable to a human eye are consolidated to obtain a normalized color space. The normalized color space is organized into swatch buckets to obtain a normalized three-dimensional color nesting cube. Each cube of the normalized three-dimensional color nesting cube represents a unique mapping code of the universal digital color standard.

RELATED APPLICATIONS

The present application claims benefit of Provisional Application No.63/113,187 filed Nov. 12, 2020 and is continuation-in-part applicationof application Ser. No. 16/594,102 filed Oct. 7, 2019, which is acontinuation of |application Ser. No. 15/472,242 filed Mar. 28, 2017,now U.S. Pat. No. 10,460,475, which is a continuation-in-part ofapplication Ser. No. 15/257,858 filed Sep. 6, 2016, now U.S. Pat. No.9,607,404, which is a continuation-in-part of application Ser. No.14/808,108 filed Jul. 24, 2015, now U.S. Pat. No. 9,436,704, which is acontinuation-in-part of application Ser. No. 14/055,884 filed Oct. 17,2013, now U.S. Pat. No. 9,348,844, which is a continuation ofapplication Ser. No. 13/910,557 filed Jun. 5, 2013, now U.S. Pat. No.8,600,153, each of which is incorporated herein by reference in itsentirety.

Application Ser. No. 13/910,557 is a continuation-in-part of applicationSer. No. 13/762,160 filed Feb. 7, 2013, a continuation-in-part ofPCT/US13/25135 filed Feb. 7, 2013, a continuation-in-part of applicationSer. No. 13/762,281 filed Feb. 7, 2013, a continuation-in-part ofPCT/US13/25200 filed Feb. 7, 2013, a continuation-in-part applicationSer. No. 13/857,685 filed Apr. 5, 2013, and a continuation-in-part ofPCT Application No. PCT/US13/35495 filed Apr. 5, 2013, each of which isincorporated herein by reference in its entirety.

Application Ser. No. 13/857,685 is a continuation-in-part of applicationSer. No. 13/762,160 filed Feb. 7, 2013, and a continuation-in-part ofapplication Ser. No. 13/762,281 filed Feb. 7, 2013, each of which isincorporated herein by reference in its entirety.

Application Ser. No. 13/910,557, application Ser. No. 13/857,685,PCT/US13/35495, each of which claims benefit of Provisional ApplicationNo. 61/656,206 filed Jun. 6, 2012, Provisional Application No.61/679,973 filed Aug. 6, 2012, and Provisional Application No.61/792,401 filed Mar. 15, 2013, each of which is incorporated herein byreference in its entirety.

Application Ser. No. 13/762,281, application Ser. No. 13/762,160,PCT/US13/25135 and PCT/US13/25200, each of which claims priority toProvisional Application No. 61/595,887 filed Feb. 7, 2012, ProvisionalApplication No. 61/656,206 filed Jun. 6, 2012, and ProvisionalApplication No. 61/679,973 filed Aug. 6, 2012, each of which isincorporated herein by reference in its entirety.

PCT/US13/35495 claims priority to application Ser. No. 13/762,160,application Ser. No. 13/762,281, each of which is incorporated herein byreference in its entirety.

FIELD OF THE INVENTION

The claimed invention relates to a normalization of color, moreparticularly, a system and method for normalizing color from a capturedimage into a universal digital color system for specification andmatching.

BACKGROUND OF THE INVENTION

At times, a user will want to search for a product by color even thoughit is an attribute that cannot be described adequately using words ornumbers that represent digital color coordinates that are notdistinguishable to the human eye. For example, other than usingrudimentary color names, such as “red” and “blue,” searching forproducts of a particular shade using color as a parameter is extremelydifficult, even when the color is relatively popular and intuitivelyshould be easy to locate. For example, there are numerous colors whichwould fit the simple “red” or “blue” description and searching using thetextual word “red” is not likely to bring up the specific red or thespecific product of interest. Also, searches based on a particular typeof color by name, such as “rose red” or “ocean blue,” are unlikely toturn up the color of interest, as there may be a number of differentcolors, each with a different name or with multiple names varying by thenaming convention used. Similarly, searching for a pattern made ofcolors, such as “blue and red stripes” is unlikely to turn up thedesired pattern of particular colors.

Many of the drawbacks involving color-based searching stem from thenature of internet searching, which has historically been text-based,thus requiring a user to enter text into a search engine to describe theinformation sought. With regard to color, textual color names aretypically tagged or embedded beneath an image of a product or associatedwebpage as metadata, making it virtually impossible to obtain reliableand complete search results when specific color shades are sought. Morespecifically, because many search systems that implement searching basedon a color (or a pattern) are operable only as text searching, a systemmay allow a user to select a color by name or even “click” on the color(in the form of a color swatch) and then search for the selected color.However, in these instances, the system typically converts the inputtedsearch parameter to a text-string associated with or representing aparticular color. For example, a search system may search based onclicking red swatch on a webpage but converts the click to a search for“red” as text, but not as an actual color. In such a system, the name ofthe color “red” is “tagged” to an image by way of a text string and thesearch is based on matching the input “red” to the text string “red” onthe tag, and not to the color. From a consumer's perspective, such asystem is insufficient to reliably capture all relevant products thatare currently available in the particular shade of red that are beingsought. From a Merchant perspective, such a system does not allow fordynamic analysis or codification of color that is a crucial but missingdata set in understanding consumer preferences.

Even color systems that offer naming conventions suffer from underlyingdrawbacks in their inconsistent application by Merchant users and theirvendors. For example, a wholesale buyer for a retailer may decide toorder a line of products from a vendor in a color that is identified as“cobalt blue.” A second wholesale buyer at the same retailer may orderanother line of products from a second vendor in a color that the secondbuyer also identifies “cobalt blue,” having the intention that thecolors be precisely the same so that a purchaser of product from thefirst line will be more inclined to purchase the second line of productas a matching set. Indeed, the variation in color between two productsthat purportedly have the ‘same color’ can be remarkable when theproducts are placed side by side. The lack of consistency among vendorsand suppliers, even when the same color names are utilized, is often notappreciated until after the products arrive, at which time it is toolate to ameliorate the situation.

Direct searching based on a particular color or a swatch has not beeneffectively accomplished with text-based systems or search systems thatlack a universal color system. For example, if a user is in possessionof one article of clothing and wishes to purchase a matching item,existing tools leave the user with the burden of determining the colorof the clothing and what a matching color might be. Thus, the user isleft to matching based on what “appears” to match (subject to variationsin color on a screen).

Current systems further lack the ability to aggregate a user's preferredand/or customized colors onto a unified area or palette for purposes ofidentifying and searching for products. Individuals typically havepreferred colors, and it would be beneficial to have that group ofpreferred colors collected and readily available to that user in asingle palette. Also, use of the palette for forming color combinationsand to perform searches based on a primary color and a secondary color(and a pattern) are lacking in the prior art. To that end, it would bebeneficial to have that group of preferred colors identified, collectedand readily available to that user in a single palette for effectivecolor-based searching. Since these searches are presently unavailable,the data associated with these searches is also unavailable to be usedfor any data analytics, real-time or otherwise. Such data analyticswould be useful to merchants and/or manufacturers for both marketing andoperations purposes. These analytics could relate to user preferencesfor colors and patterns by analyzing user browsing and purchasingbehavior, and with associated user data, such as demographic data. Suchinformation can be made available across a variety of user variables(e.g., gender, age, geography, etc.).

In addition to the deficiencies and drawbacks of current systems forconsumers, there are many related deficiencies for merchants, retailers,wholesalers and/or manufacturers as well. To start, the captured datacan be used for targeted or micro-targeted advertising based on, forexample, user preferences, preferences of affinity group members, oruser purchase/browsing history.

While current inventory management systems (IMS) include inventoryreporting and analysis, and current supply chain management (SCM)systems include production reporting, the merchants, retailers,wholesalers and/or manufacturers currently lack real-time consumerrelated data to properly forecast and respond to color-trending data.Because of its ability to identify histories of user browsing andpurchases in combination with user demographics, the claim inventionallows Merchants to forecast color trends in real time and determine, byproduct and demographics, which colors will be most successful, and plansupply chain and inventory management accordingly. Retailers andmanufacturers currently rely on focus groups, which can include as manyas 30,000 people in the relevant demographics and geo-locations tosample and obtain user color information. Such an effort is bothtime-consuming and costly. Because gathering and analyzing of data fromthe group can take up to eighteen months, once a sampling is complete,the data may no longer be relevant. The SCM must be adjusted inreal-time to create the appropriate adjustments during the manufacturingprocess. More and more retailers and wholesalers are working with “justin time” inventory, shifting the onus from the retailer to the vendor orthe factory. Adjustments in the SCM are the only solution to theinventory problems. Thus, by capturing user preferences based off of apurchase history, browsing history, word association, and colorselections, all captured in real time, a relevant collection of data maybe obtained and used by Merchants to enhance the consumer experience andstreamline operations.

OBJECT AND SUMMARY OF THE INVENTION

Therefore, it is an object of the claimed invention to provide a systemfor normalizing, codifying, tracking and categorizing color-basedproduct and data based a universal color language/system.

Another object of the claim invention is to provide aforesaid systemthat performs efficient color-based and product-related searches in theMerchants' inventory management systems (IMS) and/or supply chainmanagement (SCM) systems that have been categorized and reverse mappedinto RGB and hexadecimal codes of the universal color language/system.

A still another object of the claimed invention is to providecategorized, codified and normalized database(s) of products that bothMerchants and consumers can search for and match products usingnon-textual or color-based queries.

A yet another object of the claimed invention is to provide aforesaidsystem and method that can search for products in aforesaid database(s)based on color and patterns in the product image data.

Still another object of the claimed invention is to provide a system andmethod to normalize the digital color space into a mapping language thatis more discernable to the human eye, displays in a more organized andusable fashion on a monitor, is simpler than digital codes to write anddecipher, conveys meaning, is teachable to a machine, and is trackableacross the entire product ecosystem.

In accordance with an exemplary embodiment of the claimed invention, asystem is provided for normalizing, codifying, and categorizingdivergent color systems into a universal color language/system. A serverconnected to a communications network receives, processes, codifies andcategorizes the divergent color data from a Merchant system. Amiddleware engine of the server receives a data feed comprising aplurality of color swatches or images from the Merchant system, andnormalizes the data feed into a common format. An image segmentationprocessor of the server extracts the image data comprising a pluralityof product images from the normalized data feed, and segments eachproduct image into a plurality of segments. A dominant color processorof the server analyzes each segment to determine a dominant color foreach segment, and determines at least one dominant product color foreach product image based on prevalence of at least one dominant productcolor. A matched color processor of the server converts at least onedominant product color to a digital value based on color componentintensity values, and assigns a hexadecimal code of the universal colorlanguage/system to each product image that is closest to the digitalvalue of each product image. A product categorization engine of theserver categorizes each product image into one of a plurality of productcategories. A database stores the data feed, each product image, eachsegment of each product image, the dominant color for each segment, atleast one dominant product color for each product image, the digitalvalue and the hexadecimal code of each product image, and the productcategory of each product image.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid product categorization engine further categorizes each productimage in accordance with at least one product related data and furthercategorizes each product image in accordance with at least onedepersonalized product related data.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid matched color processor determines an Euclidian distancebetween the digital value and each hexadecimal code of the universalcolor language/system based on their color component intensity values.The matched color processor assigns the hexadecimal code yielding ashortest Euclidian distance to said each product image by the matchedcolor processor.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid middleware engine receives data feeds from a plurality of SCMsystems over the communications network. The server generates a productdatabase from data feed received from the SCM systems indexed andsearchable by color-based queries.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid middleware engine depersonalizes the data feeds received fromthe supply chain management systems to remove Merchant or supplieridentifying information.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid middleware engine receives data feeds from a plurality ofinventory management systems over the communications network. The servergenerates a product database from data feed received from the inventorymanagement systems indexed and searchable by color based queries.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid middleware engine depersonalizes the data feeds received fromthe inventory management systems to remove Merchant or consumeridentifying information by the middleware engine.

In accordance with an exemplary embodiment of the claimed invention, acolor search engine of the server receives a color-based search querycomprising user's color selection from a processor-based client deviceassociated with a user over the communications network. The user's colorselection comprises at least one hexadecimal color code of the universalcolor language/system. The color search engine searches a databaseengine for products having the hexadecimal color codes within apredetermined range of the hexadecimal color code of the user's colorselection to provide a search result. The user's color selection and thesearch result are stored in the database, and the color preferencehistory of the user is updated in the database.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid color search engine searches at least one of the following: adata warehouse maintained by a service provider, IMS of a plurality ofMerchants and SCM systems of a plurality of Merchants.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid color search engine ranks the products on the search resultbased on their hexadecimal color codes. A product having the hexadecimalcolor code closer to the hexadecimal color code of the user's colorselection is ranked higher than a product having the hexadecimal colorcode further from the hexadecimal color code of the user's colorselection.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid server receives textual search criteria from the client deviceover the communications network. The textual search criteria cancomprise at least one of the following: product description, productavailability, size information, merchant information, product category,brand information, pattern information, complementary colors orcomplementary colored products. The text search criteria could be partof a specification or spec sheet or embedded in illustration as part ofthe image analysis performed by the image analytics processor or system.The color search engine filters the search results based on the textualsearch criteria.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid product categorization engine categorizes the search resultbased on color and product category by the product categorizationengine; and stores the categorized search result in the database.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid product categorization engine further categorizes the searchresult in accordance with at least one product related data, and furthercategorizes the search result in accordance with at least onedepersonalized product related data.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid color search engine receives a color-based search query fromthe client device associated with the user over the communicationsnetwork. The color-based search query comprises a digital image of anitem and the hexadecimal color code associated with the item. The imagesegmentation processor segments the digital image of the item into aplurality of segments. The dominant color processor analyzes eachsegment to determine a dominant color for each segment, and determinesat least one dominant product color for the digital image of the itembased on prevalence of at least one dominant product color in eachsegment. The matched color processor converts at least one dominantproduct color to a digital value based on color component intensityvalues, and assigns a hexadecimal code of the universal colorlanguage/system to the digital image of the item that is closest to thedigital value of each product image. An image processor of the serverdetermines whether the hexadecimal code determined from the digitalimage of the item matches or is within a predetermined threshold of thehexadecimal code of the item received from the client device of theuser.

The claimed invention may stand on its own or serve as an enhancement ofor upgrade to existing IMS and/or SCM systems directed to facilitating awide range of functions, including search, product selection, purchase,marketing, advertising, product planning and sales. The claimedinvention can apply operations research principles to selected problemsin retailing by organizing and identifying products according to colorand/or pattern and by using those attributes as primary indicators,where retailing extends from product development and manufacturingthrough customer service, inception to sale.

In accordance with an exemplary embodiment of the claimed invention,aforesaid system can be utilized to dynamically analyze codifiedcolor-based preferences, trends and system-wide activities to maketargeted and micro-targeted product recommendations to users with coloras a primary product attribute.

Generally, the claimed invention provides a system and a set ofinterfaces that provide users and Merchants with a number of previouslyunavailable opportunities and tools in the context of coloridentification, selection and matching. The non-textual color searchesutilizing the universal color codes provide users with relevant searchresults for a number of merchant products that correlate more closely(or exactly) to the colors for which a user is searching.

With respect to the hardware of the system, CPU-based servers arearranged to communicate with one another and with one or more datawarehouses, preferably residing therein, which are used to store userdata, merchant data, product data, and color data.

In accordance with an exemplary embodiment of the claimed invention, acomputer-implemented method for normalizing a digital image into auniversal digital color system comprises obtaining a digital image of acolor swatch by a client device associated with a user and convertingthe digital image into a RGB color image of the color swatch by aprocessor of the client device. The RGB color image of the color swatchis segmented into a plurality of segments by an image segmentationprocessor of the client device. Each segment is analyzed to determine adominant color for said each segment by a dominant color processor ofthe client device. At least one dominant product color for the RGB colorimage of the color swatch is determined based on prevalence of at leastone dominant product color in each segment by the dominant colorprocessor. A hexadecimal code of the universal color system is assignedto the digital image of the color swatch that is closest to a digitalhexadecimal value of the color swatch based on color component intensityvalues of at least one dominant product color of the color swatch by amatched color processor, thereby normalizing the color swatch to theuniversal color system. The digital image of the color swatch, the RGBimage of the color swatch, at least one dominant color of the colorswatch, and the hexadecimal code assigned to the color swatch are storedin a memory of the client device.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises a step of transmitting the digitalimage of the color swatch and the hexadecimal code assigned to thedigital image of the color swatch to another client device over acommunications network by the client device.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises the steps of determining an Euclidiandistance between each hexadecimal code of the universal color system thedigital hexadecimal value of the RGB image of the color swatch based onthe color component intensity values; and assigning the hexadecimal codeyielding a shortest Euclidian distance to the RGB image of the colorswatch by the matched color processor.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises the step of determining the dominantcolor of said each segment on a pixel by pixel basis by the dominantcolor processor, the color appearing most frequently across all pixelsbeing designated as the dominant color of said each segment.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises a step of transmitting the digitalimage of the color swatch, the RGB image of the color swatch, said atleast one dominant product color for the RGB image of the color swatch,and the hexadecimal code assigned to the digital image of the colorswatch to a processor-based server over a communications network by theclient device.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises a step of determining the hexadecimalcode assigned to the digital image of the color swatch matches ahexadecimal code of one of standard color swatches.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises steps of accepting the color swatchin response to a determination that the hexadecimal code assigned to thedigital image of the color swatch matches the hexadecimal code of one ofthe standard color swatches; and rejecting the color swatch in responseto a determination that the hexadecimal code assigned to the digitalimage of the color swatch does not match the hexadecimal code of any ofthe standard color swatches.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises a step of transmitting either anacceptance message or a rejection message to another client device overa communications network by the client device.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises a step of determining the hexadecimalcode assigned to the digital image of the color swatch is within apredetermined range of a hexadecimal code of one of standard colorswatches.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid method further comprises a step of accepting the color swatchin response to a determination that the hexadecimal code assigned to thedigital image of the color swatch is within the predetermined range; andrejecting the color swatch in response to a determination that thehexadecimal code assigned to the digital image of the color swatch isnot within the predetermined range.

In accordance with an exemplary embodiment of the claimed invention, aclient device to normalize a digital image into a universal digitalcolor system comprises a camera to acquire a digital image of a colorswatch and a processor. The processor converts the digital image into aRGB color image of the color swatch. The RGB color image of the colorswatch is segmented into a plurality of segments and each segment isanalyzed to determine a dominant color for each segment. At least onedominant product color for the RGB color image of the color swatch isdetermined based on prevalence of at least one dominant product color ineach segment. A hexadecimal code of the universal color system isassigned to the color swatch that is closest to a digital hexadecimalvalue of the RGB image of the color swatch based on color componentintensity values of at least one dominant product color of the colorswatch, thereby normalizing RGB colors of the color swatch. The digitalimage of the color swatch, the RGB image of the color swatch, at leastone dominant product color of the color swatch, and the hexadecimal codeassigned to the color swatch are stored in a memory.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid the client device comprises a network connection facility totransmit the digital image of the color swatch and the hexadecimal codeassigned to the digital image of the color swatch to another clientdevice over a communications network.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid processor determines an Euclidian distance between eachhexadecimal code of the universal color system the digital hexadecimalvalue of the RGB image of the color swatch based on the color componentintensity values. The hexadecimal code yielding a shortest Euclidiandistance to the RGB image of the color swatch is assigned.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid processor determines the dominant color of said each segmenton a pixel by pixel basis, the color appearing most frequently acrossall pixels being designated as the dominant color of each segment.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid client device comprises a network connection facility totransmit the digital image of the color swatch, the RGB image of thecolor swatch, at least one dominant product color for the RGB image ofthe color swatch, and the hexadecimal code assigned to the color swatchto a processor-based server over a communications network.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid processor determines whether the hexadecimal code assigned tothe digital image of the color swatch matches a hexadecimal code of oneof standard color swatches.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid client device comprises a screen that displays an acceptancemessage in response to a determination that the hexadecimal codeassigned to the digital image of the color swatch matches thehexadecimal code of one of the standard color swatches, and displays arejection message in response to a determination that the hexadecimalcode assigned to the digital image of the color swatch does not matchthe hexadecimal code of any of the standard color swatches.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid client device comprises a network connection facility totransmit either the acceptance message or the rejection message toanother client device over a communications network.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid processor determines whether the hexadecimal code assigned tothe digital image of the color swatch is within a predetermined range ofa hexadecimal code of one of standard color swatches.

In accordance with an exemplary embodiment of the claimed invention, theaforesaid client device is one of the following: a smartphone, a tablet,a laptop, a netbook or a network-enabled device with a camera.

In accordance with an exemplary embodiment of the claimed invention, anon-transitory computer readable medium comprises computer executablecode for normalizing a digital image into a universal digital colorsystem. The computer executable code comprising instructions forobtaining a digital image of a color swatch by a client deviceassociated with a user and converting the digital image into a RGB colorimage of the color swatch by a processor of the client device. The RGBcolors of the RGB color image of the color swatch is normalized bysegmenting the RGB color image of the color swatch into a plurality ofsegments by an image segmentation processor of the client device. Eachsegment is analyzed to determine a dominant color for said each segmentby a dominant color processor of the client device. At least onedominant product color for the RGB color image of the color swatch isdetermined based on prevalence of said at least one dominant productcolor in each segment by the dominant color processor. A hexadecimalcode of the universal color system is assigned to the digital image ofthe color swatch that is closest to a digital hexadecimal value of theRGB image of the color swatch based on color component intensity valuesof at least one dominant product color of the RGB color image of thecolor swatch by a matched color processor.

In accordance with an exemplary embodiment of the claimed invention, acomputer-implemented method for normalizing a RGB (red, green, blue)digital color space into a universal digital color standard is provided.The RGB digital color space is mapped into a three-dimensional colorcube. The sides of the three-dimensional color cube get progressivelysmaller until the sides converge in a center point of thethree-dimensional color cube to form a three-dimensional color nestingcube. Duplicate colors in the RGB digital color space that are notdistinguishable to a human eye are consolidated to obtain a normalizedcolor space. The normalized color space is organized into swatch bucketsto obtain a normalized three-dimensional color nesting cube. Each cubeof the normalized three-dimensional color nesting cube represents aunique mapping code of the universal digital color standard.

Various other objects, advantages and features of the present inventionwill become readily apparent from the ensuing detailed description, andthe novel features will be particularly pointed out in the appendedclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

The above-described and other advantages and features of the presentdisclosure will be appreciated and understood by those skilled in theart from the following detailed description and drawings of which:

FIG. 1 is a block diagram of the system in accordance with an exemplaryembodiment of the claimed invention;

FIG. 2 is a block diagram of the server in accordance with an exemplaryembodiment of the claimed invention;

FIGS. 3A and 3B together comprise an exemplary system diagram depictinginteraction among various system components to normalize, analyze andcodify divergent Merchants' color systems into a single universal colorlanguage/system in accordance with an exemplary embodiment of theclaimed invention;

FIG. 4 is block diagram of the client device in accordance with anexemplary embodiment of the claimed invention

FIG. 5 is an exemplary flow chart depicting the dynamic color analysisof codifying, categorizing and reverse mapping a Merchant's color systemto the claimed single universal color language/system by the colorengine in accordance with an exemplary embodiment of the claimedinvention;

FIG. 6 is block diagram of the color engine in accordance with anexemplary embodiment of the claimed invention;

FIG. 7 is a flow chart depicting an exemplary process for normalizing,categorizing and codifying divergent colors from a plurality of MerchantIMS/SCM systems into a single universal color language/system inaccordance with an exemplary embodiment of the claimed invention;

FIGS. 8a through 8g illustrate an exemplary process for identifying andrecognizing color(s) and/or pattern(s) from an image of a striped shirtpattern by the image analytics processor in accordance with an exemplaryembodiment of the claimed invention;

FIG. 9 is a flow chart depicting an exemplary process for extractingcolor data by segmenting the product image into a plurality of regionsin accordance with an exemplary embodiment of the claimed invention;

FIG. 10 illustrates an exemplary four-quadrant framework, eachsubdivided into a 16×16 grid into which a swatch or image is divided forprocessing by the color engine in accordance with an exemplaryembodiment of the claimed invention;

FIG. 11a illustrates an exemplary grayscale representation of a red andblack checkered pattern for color and pattern recognition by the colorengine in accordance with an exemplary embodiment of the claimedinvention;

FIG. 11b illustrates an exemplary grayscale representation of a rotatedred and black checkered pattern for color and pattern recognition by thecolor engine in accordance with an exemplary embodiment of the claimedinvention;

FIG. 11c illustrates an exemplary grayscale representation of apartially distorted red and black checkered pattern for color andpattern recognition by the color engine in accordance with an exemplaryembodiment of the claimed invention;

FIG. 12 is a flow chart depicting an exemplary process for identifyingand recognizing color(s) and/or pattern(s) by the image processor inaccordance with an exemplary embodiment of the claimed invention;

FIG. 13 illustrates an exemplary user registry page and an exemplaryflow diagram depicting interaction among various system components toperform color based search for primary and secondary users in accordancewith an exemplary embodiment of the claimed invention;

FIG. 14 illustrates an exemplary graphical user interface or display forcolor search access in accordance with an exemplary embodiment of theclaimed invention;

FIG. 15 is an exemplary flow diagram depicting interaction among varioussystem components to perform color based search in accordance with anexemplary embodiment of the claimed invention;

FIG. 16 is an exemplary flow diagram depicting an exemplary process foranalyzing colors for quality control in accordance with an exemplaryembodiment of the claimed invention;

FIG. 17 is an exemplary flow diagram depicting an exemplary process foranalyzing colors for quality control in accordance with an exemplaryembodiment of the claimed invention;

FIG. 18 is an exemplary flow diagram depicting an exemplary process foranalyzing colors for quality control in accordance with an exemplaryembodiment of the claimed invention;

FIG. 19 is an exemplary flow chart depicting an exemplary dynamicprocess of categorizing a merchant's color system to the claimed singleuniversal color language/system by color, product category anddepersonalized product related data in accordance with an exemplaryembodiment of the claimed invention;

FIG. 20 is an exemplary flow chart depicting an exemplary dynamicprocess of categorizing a merchant's color system to the claimed singleuniversal color language/system by color, product category andpersonalized product related data in accordance with an exemplaryembodiment of the claimed invention;

FIG. 21 is an exemplary flow chart depicting an exemplary dynamicprocess of normalizing, codifying and categorizing Merchants' IMS andSCM data feeds, and categorizing search results;

FIG. 22 is an exemplary flow chart depicting an exemplary dynamic systemprocess of normalizing, codifying and categorizing Merchants' IMS andSCM data feeds, and categorizing search results;

FIG. 23 is an exemplary flow chart depicting a process for normalizing acaptured digital image in accordance with an exemplary embodiment of theclaimed invention;

FIG. 24 is an exemplary flow chart depicting a process for normalizing acaptured digital image and comparing the normalized captured image to astored, normalized colored swatch in accordance with an exemplaryembodiment of the claimed invention;

FIG. 25 illustrates a normalized digital color nesting cube inaccordance with an exemplary embodiment of the claimed invention;

FIG. 26A-C illustrate exemplary hue axis corners of the normalizeddigital color nesting cube in accordance with an exemplary embodiment ofthe claimed invention;

FIG. 27A-C illustrate exemplary layer bar and color saturation of thenormalized digital color nesting cube in accordance with an exemplaryembodiment of the claimed invention;

FIG. 28 illustrates an exemplary grid for a swatch bucket display of thenormalized digital color nesting cube in accordance with an exemplaryembodiment of the claimed invention;

FIG. 29A-B illustrate exemplary color mapping codes of the normalizeddigital color nesting cube in accordance with an exemplary embodiment ofthe claimed invention;

FIG. 30A-C illustrate exemplary color blind mapping codes of thenormalized digital color nesting cube in accordance with an exemplaryembodiment of the claimed invention; and

FIG. 31 is an exemplary flow chart depicting a process for color mappingand machine learning to color coordinate products, patterns and objectson a homogenized eCommerce platform in accordance with an exemplaryembodiment of the claimed invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

In accordance with an exemplary embodiment of the claimed invention,non-textual color-based systems and interfaces are provided tocategorize, normalize and dynamically analyze color-based product anddata based on a unified or universal color system as described inapplicant's U.S. application Ser. No. 13/910,557 (now U.S. Pat. No.8,600,153), pending U.S. application Ser. No. 14/055,884 (now U.S. Pat.No. 9,348,844) and international Application No. PCT/US13/44317(hereinafter collectively referred to herein as “applicant'snormalization/codification application”), each of which is incorporatedherein by reference in its entirety. To categorize and analyze massiveamounts of data across a diverse range of product categories requires acommon denominator or attribute that all products have in common. Coloris that common denominator provided that all colors have been reversemapped from divergent color systems, normalized and converted into auniversal color (or digital color) system, as exemplary described inapplicant's normalization/codification application. Accordingly, theclaimed invention proceeds upon desirability providing a digitalcolor-based categorization for data analytics.

In accordance with an exemplary embodiment of the claimed invention, theclaimed color-based system collects, analyzes and manages color data,non-color data, such as textual product data, and anonymous andnon-anonymous user and merchant data, to provide a more robust productsearching and purchase experience for users and a more effective meansfor Merchants to target, advertise and sell to consumers.

In accordance with an exemplary embodiment of the claimed invention, thesystem obtains data from a plurality of sources, developing businessintelligence, real time data analytics, and predictive analytics fromthe obtained data, and providing services to consumers as well as aplurality of business types of users with respect to the developedbusiness intelligence and “Big Data”. In general, the data relate to (1)particular characteristics of purchasable products where at least one ofthe characteristics includes or relates to color, (2) consumers'preferences, and their actual and potential purchases, and (3) inventoryand potential inventory of stores, including colors and sizes. Further,the claimed invention is extendable to include future inventoryinformation derived from Supply Chain Management (SCM systems 510),including but not limited to previews of new products that are indevelopment or in production.

In accordance with an exemplary embodiment of the claimed invention, thesystem of the claimed invention is directed to in-store inventorycontrol and to assuring that likely purchases are available and visiblein-store. In addition, the present invention leverages connectivitybetween a recipient's inventory control system and its manufacturers,distributors, and designers so as to expedite requested or anticipatedinventory changes.

In another embodiment, the system of the claimed invention is directedto identifying likely and/or potential purchasers of particular products(including groups of products or products of a particular color) andoffering Merchants an opportunity for targeted (or micro-targeted)advertising toward those likely and/or potential purchasers.

Turning to FIG. 1, in accordance with an exemplary embodiment of theclaimed invention, there is shown an exemplary system configurationcomprising a processor-based system 100, such as one or more computersor servers 100, with the hard disk or memory drives running softwarecomprising machine-readable program instructions. The server 100 servesas and/or provides access to the data warehouse 200, which comprises theproduct database 206 and the color database 208. Preferably, the datawarehouse 200 also comprises the user database 202 and the merchantdatabase 204. All data are maintained in the data warehouse 200 or otherconventional database system having read and write accessibility using adatabase management system. Although described herein for illustrativepurposes as being separate data stores, in at least some alternativeembodiments, the data stores may be combined in various combinations.

Information contained in the data warehouse 200 is accessible by bothconsumer and Merchant users via the client devices 300 over acommunications network 400, such as the Internet 400. The client devices300 comprise processor-based machine(s), such as laptops, PCs, tablets,smart phones and/or other web-enabled handheld devices to and from whichthe server 100 communicates. In accordance with an exemplary embodimentof the claimed invention, as exemplary shown in FIG. 4, the clientdevice 300 comprises a processor 320, an optional camera 310, a memory330, a display 340, a network connection facility 350 and an inputdevice 360. The client devices 300 are connected to the server 100utilizing customizable interfaces described herein. The custominterfaces may be in the form of a graphical user interface, anapplication to form a client-server arrangement and/or other well-knowninterface conventions known in the art. Depending on the nature of theuser and its access to various forms of information, differentinterfaces are made available. To support various options, the system ofthe present invention preferably includes at least oneapplication-programming interface (API) so that certain types of userscould enhance their interfaces, and different ones may be available forusers and Merchants.

In accordance with an exemplary embodiment of the claimed invention, thesubscribers (consumer or Merchant users, etc.) gain entry to the server100 by subscription using known security methodologies, e.g., usernameand password combination. Once a subscriber is authenticated, the server100 provides access to the data that the subscriber can rightfullyaccess.

In accordance with an exemplary embodiment of the claimed invention, theserver 100 stores/maintains hexadecimal and RGB color code oridentification information and pattern identification information in thecolor database 208. Each individual color identification entrycorresponds to one of a plurality of uniform/universal colors stored inthe color database 208 and each individual pattern identification entrycorresponds to one of a plurality of selectable patterns stored in thecolor database 208. The image processor 180 of the server 100dynamically analyzes the color and pattern identification information todetermine and associate dominant colors and patterns with a particularproduct. It is appreciated that for certain resource intensiveapplications, such as processing a large volume of feeds 505, 515 frommultiple Merchants, as shown in FIG. 6, the claimed system can compriseone or more separate color engine(s) 550 for performing the dynamicimage/swatch analysis 560 instead of the image processor 180. Due to itscommon functionalities, the color engine 550 and the image processor 180is used interchangeably herein.

As more fully described in applicant's normalization/codificationapplication, the server 100 receives product information (i.e., feeds)over the communications network 400 from a plurality of Merchants. Theserver 100 receives the feeds from retailers', wholesalers', and/ormanufacturers' inventory management systems (“IMS”) 500 or supply chainmanagement (“SCM”) systems 510. It is appreciated that for simplicitymerchants, retailers, wholesalers and manufacturers will be collectivelyand interchangeably referred to herein as Merchants. Preferably, as newproducts are added or product information is updated in the IMS 500and/or the SCM system 510, the corresponding information is transmittedto the server 100. That is, the IMS 500 and/or SCM system 510dynamically transmit the updated information to the server 100.

SCM is the management of the flow of goods. It includes the movement andstorage of raw materials, work-in-process inventory from inception tofinished goods. SCM is defined as the design, planning, execution,control, and monitoring of supply chain activities with the objective oftaking a product from inception (design) to a finished product. Aproduct runs through the SCM system 510 and, when finished, transfersinto the IMS 500 which tracks the finished goods.

The SCM system 510 is a production based system used by factories andtheir component suppliers. Within the SCM system 510 there may be anelement of the IMS 500, which would be used to keep track of theinventory of components and raw materials. That said, the SCM system 510is strictly a B2B (business-to-business) system that does not involvethe consumer unless it is utilized for the use of “previewing” futureinventory to a consumer in order to gauge future sales and makeadjustments during the manufacturing process.

Whereas, the IMS 500 is a computer-based system for tracking inventorylevels, orders, sales and deliveries. It can also be used in themanufacturing industry to create a work order, bill of materials andother production-related documents. Companies use the IMS 500 to avoidproduct overstock and outages. It is a tool for organizing inventorydata that before was generally stored in hard-copy form or inspreadsheets.

Modern IMS 500 often rely upon barcodes and radio-frequencyidentification (RFID) tags to provide automatic identification ofinventory objects. Inventory objects can include any kind of physicalasset: merchandise, consumables, fixed assets, circulating tools,library books, or capital equipment. To record an inventory transaction,the IMS 500 uses a barcode scanner or RFID reader to automaticallyidentify the inventory object, and then collects additional informationfrom the operators via fixed terminals (workstations), or mobilecomputers.

The new trend in inventory management is to label inventory and assetswith quick response (QR) Code, and use smartphones to keep track ofinventory count and movement. These new IMS 500 are especially usefulfor field service operations, where an employee needs to recordinventory transaction or look up inventory stock in the field, away fromthe computers and hand-held scanners.

The barcodes, RFID tags and QR codes are normally implemented during theproduction process as part of the Specification Sheet (Spec Sheet) whichconveys all of the product details such as Color Code, Style Code,Vendor Code, and the information (fabric content, size, productcategory) that may be contained within any or all of these codes. TheSCM system 510 stores the Spec Sheet. The barcodes, RFID tags and QRcodes are also used as a tool to track inventory sales in the IMS 500which is done by scanning at point of sale.

Without the universal digital color language/system of the claimedinvention, color data from these various barcodes and tags cannot beidentified or defined. If the color name is “sterling blue” and theactual color is a shade of blue grey, a search for the color willproduce the tagged names unless the system is performing an imageanalysis for the precise color and ignoring the information provided bybarcodes and tags. Once the color is normalized, codified andcategorized into a single universal digital system of the claimedinvention, the same search now can be performed more effectively bysearch based on color in the normalized, codified and categorized IMS500 no matter what contextual color name is used to describe theproduct.

The claimed invention converts conventional SCM systems 510 and IMS 500into an efficient color-based system that can be efficiently searchedbased on color and product categories. The claimed system normalizes,codifies and categorizes the data stored in the various SCM systems andIMS into colors based on the universal color code, and furthercategorizes the color normalized, codified and categorized data intoproduct categories. Color is the only common denominator that allproducts have in common, the claimed invention provides a mechanism forsearching based on the universal digital color code that is shared bythe members of the supply chain management, including but not limited tomerchants, manufacturers, distributors, retailers, componentmanufacturers, etc.

Since information relating to products provided by different Merchantsis often expected to be formatted differently from one another, datareceived from various Merchants are transformed or normalized to acommon format (e.g., an image of predetermined size, such as 500 pixelsby 500 pixels), so that the information can be processed consistentlyand efficiently by the server 100. In accordance with an exemplaryembodiment of the claimed invention, a middleware engine 520 of theserver 100 receives IMS data feeds 505 and/or SCM data feeds 615comprising textual and non-textual (color) product informationrespectively from the IMS 500 and/or SCM system 510, and categorizes andnormalizes or transforms the data. The middleware engine 520 integratesand manages incoming data as the data is transmitted from the IMS 500and/or the SCM systems 510 to server 100. That is, the middleware engine520 manages the interaction between the otherwise incompatibleapplications residing on the server 100 and Merchant IMS 500 and/orMerchant SCM systems 510. Preferably, the middleware engine 520categorizes and normalizes or transforms the IMS data feeds 505 and/orthe SCM data feeds 515 into single item data format so that the data canbe efficiently organized in an item table 540.

In accordance with an exemplary embodiment of the claimed invention, themiddleware engine 520 performs digital image analysis (DMI) by ingestingor consuming programmatically flat digitally encoded images or extractedflat images from encoded digital video such as via a web-based graphicaluser interface (GUI), application program interface (API), or otherknown programmatic methods. The middleware engine 520 stores theingested data from the external feeds 505, 515, such as the IMS feed 505and/or SCM feed 515, in the data warehouse 200. As part of the ingestionprocess, the middleware 520 normalizes, categorizes and stores the datasuch that the item table 540 contains available product information fromthe proprietary Merchant IMS 500 and/or the proprietary Merchant SCMsystem 510, including textual and non-textual (color) productinformation.

By utilizing the universal color language or system for a plurality ofMerchants, the claimed invention resolves a significant hindrance touser searching for and finding products from different Merchants.Reverse mapping enables dynamic analysis and codification of precisecolor. When layered into proprietary Merchant IMS 500 and/or SCM systems510, the search performed in accordance with an exemplary embodiment ofthe claimed invention is further enhanced as it is no longer requiresscraping the Internet. Likewise, the claimed invention amelioratesissues associated with Merchant product planning and production byproviding them with standardized color information on sales, searchesand availability.

In accordance with an exemplary embodiment of the claimed invention, thesystem and interfaces described herein are designed to operate in a 4096universal color language/system or environment, but on a scale whichallows the system to expand to over 16 million universal colors usingthe full range of 256 color intensities (measured from 0 to 255) foreach of R (Red), G (Green) and B (Blue) which yields 256³ or 16,777,216possible color variations, and hence potential 16 million universalcolor codes or classifications. The claimed invention utilizes thedivergent color systems of multiple Merchants that have been reversemapped, normalized and codified into a universal system for dynamicanalysis, as described in applicant's normalization/codificationapplication. Preferably, the 4096 selectable universal colors areequidistantly spaced along the full scale of available colors. However,it should be understood that the selectable colors may be moved alongthe scale or added or subtracted in order to provide more or lessvariation in a particular color region, depending on user and Merchanttrends or needs.

In accordance with an exemplary embodiment of the claimed invention, asshown in FIG. 2, the server 100 comprises one or more processors 110, acolor search engine 120, a palette generator 130, a registry module 140,a user module 150, a product recommendation engine 160, a real-timeanalytics processor 170, an image processor 180 and a productcategorization engine 190. The server 100 obtains data from a variety ofsources. In accordance with an exemplary embodiment of the claimedinvention, the color palette generator 130 of the server 100 generatescolor palette based on the user's personal and demographic information,such as, but not limited to, name, location, birth date, preferredproducts, and preferred colors, obtained from a user/subscriber (or adifferent user/subscriber) by the user module 150 of the server 100. Theprocessor 110 of the server 100 obtains data regarding products andinventories from Merchants' IMS 500 as part of the IMS feeds 505 and/orfrom Merchants' SCM systems 510 as part of the SCM feeds 515, and thedata may be in the form of text, images, videos, or some combinationthereof.

Each data set introduced in the data warehouse 200 representsinterrelated data sets that communicate with and rely on other data setsfor complete information (but do not necessarily represent discrete datasets). These data sets may be accessed using a variety of databasemanagement systems (DBMS), including but not limited to relationaldatabase management systems (RDBMS) and “post-relational” databasemanagement systems (e.g., not only Structured Query Language (“NOSQL”)database management systems. Furthermore, by using a DBMS such as RDBMSor a “post-relational” DBMS, the data may be available to a Merchant ina variety of manners, such as based on a specific demographic profile ora specific color or color grouping.

In general, data are received from a variety of sources, with at leastsome or all data/content received using live feeds from sources. Resultsmay be sent to a variety of destinations, all related to combinations ofconsumer preferences, Merchant inventory, recent activity, andtransactions. The sources of data include stores, including theirinventory on-hand in various stores and on order, other Merchants andtheir facilities, and portions of a store or Merchant's supply chain,such as manufacturers and designers of the goods sold by thestores/Merchants, and preferably, including live feeds from each. Datasources also include consumers and financial institutions, as well asother independent sources (such as but not limited to news, weather, andmedia feeds). At least some of the data are received or obtained in realtime by the data warehouse 200, preferably using live feeds. Thereal-time analytics processor 170 can perform analysis on demand or evenas the data are being received by the server 100 and the data warehouse200. The real-time analytics processor 170 delivers the results of theanalysis in near real-time, even while the consumer is in the midst ofshopping, such as delivering guidance to consumers as they shop based onrecent inventory changes.

In accordance with an exemplary embodiment of the claimed invention, theuser database 202 maintains and stores data specific to an individualuser/subscriber, including but not limited to, personal information,demographic information, preferences, product history information, andsocial information. Personal information can include username, name,address (and more generalized geographic information), telephone data,birth date, astrological information, keywords with which the userassociates, colors with which the user associates specific keywords,etc. Demographic information can include age, gender, education history,income, marital status, occupation, religion and the like. Preferencescan include user's preference of colors, keywords with which the userassociates a particular color, books, games, hobbies, sports, sportsteams and the like. Some of the preferences can be obtained directlyfrom the user and other preferences can be determined by the user module150 of the server 100 based on user's web searches and/or purchases.Product history information can include user's browsing history, user'sproduct ratings (e.g., likes and hides), user's purchase history, user'sfavorite stores, user's favorite brands, etc. Social information caninclude user-to-user or user-to-Merchant associations including, but notlimited to, friends, family, colleague, romance, and acquaintanceassociations.

Personal information and demographic information are typically acquiredfrom a user in the context of an initial user registration process andsubsequently stored in the user database 202 which contain a broad rangeof records pertaining to user identification and user selections. Theremaining forms of user data are acquired and recorded in the userdatabase 202 as a result of user-system interactions via a graphicaluser interface.

In accordance with an exemplary embodiment of the claimed invention, themerchant database 204 maintains and stores data specifics to a Merchant,including but not limited to Merchant information, e.g., business name,contact name, address, and telephone number; demographic information,e.g., target demographics, user and Merchant demographics andpreferences; physical locations; inventory information; supply chaininformation; plan-o-gram and store schematic information; and purchasehi story information.

In accordance with an exemplary embodiment of the claimed invention,product database 206 maintains and stores data specifics for products,including but not limited to: basic product identification information,including name of product; color identification information, includinguniversal hexadecimal color code, color histogram and statisticalinformation; pattern identification information, where applicable; imagedata, preferably in the form of a three-dimensional digital rendition ofthe product or another form of digital image of the product;recommendation data, including historical recommendations of products,ratings of products and advertisement data pertaining to products; andcurrent and future product availability information. Preferably, theproduct data is indexed and categorized by product category, e.g.,tables, chairs, shoes, shirts, socks, cars, paints, etc.

It should be appreciated that the product data stored in the productdatabase 206 can be indexed, e.g., by product category, andcross-referenced in a number of useful ways by associating the productdata with specific types of user data, Merchant data and color data.Thus, various types of product data can be referenced and manipulatedutilizing, for example, any combination of color, availability, userpreference and demographic. In that way, data in the data warehouse 200is interrelated forming a powerful tool in the context of predictiveanalytics.

In accordance with an exemplary embodiment of the claimed invention,color database 208 maintains and stores data specifics for colorinformation, including but not limited to: the hexadecimal color code oridentification information; the RGB color identification information;the pattern identification information; the statistical colorinformation; the keyword information; and the color groupinginformation. The hexadecimal color code or identification information isstored in the color database 208 as color data in the form ofhexadecimal codes for each selectable color. The RGB coloridentification information is stored in the color database 208 as colordata in the form of RGB component intensities for each selectable color.Preferably, each RGB component intensity maps to a correspondinghexadecimal code. The pattern identification information is stored inthe color database 208 as color data in the form of pre-determinedpattern configurations.

The statistical color information stored in the color database 208 ascolor data provides information relating to popularity or frequency ofthe product's color, e.g., frequency of men shirts containing aparticular color. It can also provide trending information in real-timeas to which product colors were popular in the current season and whichproduct colors are forecasted to be popular in the next season basedconsumer purchases. This can be valuable to manufacturers and retailersin determining what product colors to manufacture and stock in theirstores.

The keyword information stored in the color database 208 as color datacan be frequently user-associated keywords relating to a particularcolor. The associated keywords may be based on an original color-wordassociation index; user-defined keywords whereby a user associatescolors with specific keywords; and pre-determined keywords which theuser links with colors that the user determines are associated withthose pre-determined keywords. The server 100 stores and updateskeywords and their color associations as users continue to update andcreate associations in the color database 208. Color groupinginformation stored in the color database 208 as color data can be colorsassociated with a timeless collection or a particular trendingcollection (e.g., Spring 2012 colors).

It should be appreciated that data stored in the color database 208 ascolor data can be indexed, e.g., by product category, andcross-referenced in a number of useful ways by associating color datawith specific types of user data, Merchant data and product data. Inthis way, data in the data warehouse 200 is interrelated forming apowerful tool in the context of predictive analytics.

By integrating a universal color identification technique intoproprietary IMS 500 and/or SCM systems 510, available color data can bedynamically analyzed and integrated to enable Merchants to makecolor-based decisions and recommendations on a real-time basis that wereheretofore not practical or, at best, based on incomplete information.With respect to supply chain management, inventories of products byparticular colors can be managed and prioritized and decisions toreplenish inventories can be effected sooner by triggering manufacturingand distribution as soon as, for example, certain sales thresholds aremet, inventories dip below a particular level and/or additional consumerneed is identified beyond current supply plans and capabilities.Moreover, Merchants can also advertise and give information users onexpected availability using available supply chain managementinformation. Similarly, such information can be used to allow users topre-order products. On the inventory side, inventories of availableproducts can be kept more stable by promoting products based on currentand near-term availability. Furthermore, where a particular color for aproduct is unavailable, default settings enable recommendations to bemade of the closest matching color. Thus, product search andrecommendations can be made considering both current and futureinventories.

In accordance with an exemplary embodiment of the claimed invention, asshown in FIG. 6, the color engine 550 comprises an API retrieval module910, an image segmentation processor 920, a dominant color processor 930and a pattern identification processor 940. It is appreciated that forcertain resource intensive applications, such as processing a largevolume of IMS feeds 505 and/or SCM feeds 515 from multiple Merchants,the claimed invention can comprises a multiple image processors 180 orone or more separate image server(s). The color engine 550 initiates thedynamical image analysis and color conversion process 560 by instructingthe API retrieval module 910 to retrieve the normalized and categorizedimage data from the data warehouse 200. The color engine 550 convertscolors based on component intensities to a digital value, preferably anuniversal 24-bit, 6-digit hexadecimal code which uses a base sixteennumber instead of conventional base ten numbers, two digits for each ofthe Red, Green and Blue values. Similarly, the color engine 550 canexpress colors as a concatenation of digital values for R, G and Bcomponents of a color and assigned the concatenated digital values to aproduct as a color identifier. For example, if a particular colorexhibits RGB values: 189 Red: 202 Green: 220 Blue, that number can beconverted to a hexadecimal value BDCADC. 189 corresponds to BD in hexnotation, 202 corresponds to CA in hex notation and 220 corresponds toCD in hex notation.

In accordance with an exemplary embodiment of the claimed invention, themiddleware engine 520 normalizes product data from plurality ofMerchants and the image processor 180 converts the Merchants' color datainto universal color codes, preferably, a universal hexadecimal colorcode. The product categorization engine 190 then categorizes thenormalized and color categorized product data into various productcategories. It is appreciated that universal color code can be expressedas RGB component measurements or other digital representation. That is,the color engine 550 dynamically analyzes and converts the color swatchto a universal 24-bit hexadecimal color code, thereby codifying thenon-uniform colors used by various Merchants into a universalhexadecimal color code.

In an accordance with an exemplary embodiment of the claimed invention,during the normalization process 530, the middleware engine 520 alsostrips away Merchant identification information (Merchant IDs) thatcould be used to relate product information to a specific Merchant.Also, the middleware engine 520 stores the personalized information,e.g., Merchant IDs, etc., in the personalized database 209. Also, themiddleware engine 520 stores depersonalized information in thedepersonalized database 210 by removing Merchant IDs from the data,thereby de-linking Merchant information from the products. Thiseliminates the possibility of competitors having access to sensitive orproprietary information.

As a result of previously adopted color naming conventions by a Merchantor as a result of Merchant-vendor practices which are ostensiblyincompatible with assigning a universal color code to a given product,the color data of the IMS feed 505 and/or the SCM feed 515 need to beconverted or reverse mapped to the hexadecimal color code of theuniversal color language/system. The image processor 180 performs thedynamic image/swatch analysis 560 to analyze, convert and reverse mapthe Merchant's product color to the claimed universal hexadecimal colorcode. In accordance with an exemplary embodiment of the claimedinvention, the image processor 180 receives, dynamically analyzes andconverts the Merchant's color swatch, preferably digital color swatch,alone or in combination with a Merchant color name (or names) for thatcolor swatch to an universal color code.

The middleware engine 520 transforms and normalizes the IMS feed 505and/or the SCM feed 515 comprising Merchant's color swatch andpreferably, Merchant's textual product data. In accordance with anexemplary embodiment of the claimed invention, the image processor 180or the color engine 550 performs dynamic image/swatch analysis 560 onthe normalized data received from the middleware engine 520 to determineits dominant color(s) and/or pattern(s). As shown in FIGS. 3A, 3B, 5-7,the image processor 180 or the color engine 550 gathers and dynamicallyprocesses the image or color swatch present in the proprietary Merchantdata feeds 505, 515 to determine and map the color swatch to anuniversal color code. The image processor 180 or the color engine 550dynamically analyzes the color swatch to determine and store thedominant color(s) and pattern(s) as color data 208 in data warehouse200.

In accordance with an exemplary embodiment of the claimed invention, asshown in FIGS. 5 and 8, the image processor 180 or the color engine 550dynamically analyzes images or swatches of the products received as partof the IMS data feeds 505 and/or SCM data feeds 515 respectively fromthe Merchant's IMS 500 and/or Merchant's SCM system 510 to determine thecolor(s) and/or pattern(s) of Merchant's products. Although the imageprocessing is described herein with the IMS data feeds 505, it isappreciated that the image processor 180 performs similar analysis onthe SCM data feed 515. The image processor 180 stores the universalcolor code obtained as a result of the analysis as color data in thecolor database 208. That is, the image processor 180 extracts colorinformation from the IMS data feed 505 to codify or map the Merchant'sproduct color (i.e., Merchant's color swatch) to a universal color code.As shown in FIG. 5, at step 551, the server processor 110 receives acolor swatch or image of the product as a normalized data input from theMerchant's IMS 500, preferably via the middleware engine 520. The imageprocessor 180 buffers the color swatch at step 552 and divides the colorswatch into a plurality of sub-images to determine the dominant colorsat step 554. Thereafter, the image processor 180 determines the dominantcolor(s) of each sub-image at step 556 to assign a numerical colorvalue, preferably, a hexadecimal value, to the color swatch. The imageprocessor 180 also determines and stores a color histogram andstatistical data that may include detailed RGB band information,including the mean, standard deviation and minimum value and maximumvalue associated with each of the RGB bands, at step 558.

In accordance with an exemplary embodiment of the claimed invention, theimage processor 180 categorizes products associated with the analyzedcolor swatch of the Merchant's product, at step 559. That is, the imageprocessor 180 categorizes Merchant's products by color, preferably bythe hexadecimal color code or value of the universal colorlanguage/system. As exemplary shown in FIGS. 19-20, the productcategorization engine 190 of the server 100 determines the productcategory of the color analyzed product, e.g., clothing, furniture, car,etc., at step 561, and categorizes the color analyzed product by productcategory based on the product information retrieved or received from thedata warehouse 200 and/or the IMS 500 and/or SCM systems 510, at step562. The source of the product information can be from the specificationsheet, which can include product specification, product category, colorrange, etc. For normalized data feed, the source of the productinformation can be from the formatted specification sheet. In additionor alternatively, the product categorization 190 may utilize the imageprocessor 160 to analyze the product image to determine the productcategory. The product categorization engine 190 can further categorizethe color analyzed/categorized product by other personalized ordepersonalized product information or product related data at step 563.The product categorization engine 190 categorizes based on suchdepersonalized information as size, material, price, geographicallocation of the product, etc. or based on personalized information suchas user name, store name, brand name, age, gender, etc. It isappreciated that the personalized information can include one or more ofthe depersonalized information. Accordingly, the data warehouse 200contains products categorized by color, products and other personalizedand/or depersonalized product related data, thereby facilitating dynamiccolor search based on a universal color language/system.

While swatches or images that contain a single dominant color are easierto classify by color, there are many instances where the image processor180 must parse an image to make accurate color and/or patterndeterminations. The dynamic image analysis of Merchant's color swatchesor images with multi-colored patterns can be resource intensive for theimage processor 180 to extract the necessary color information.Depending on the volume of images received from the Merchant's IMS 500and/or the Merchant's SCM system 510, a dynamic resource server or acluster of dedicated servers 100 may be required to provide thenecessary computational power, memory and storage to normalize, analyzeand codify the IMS data feeds 505 and/or SCM data feeds 515 containingthese images or color swatches.

In accordance with an exemplary embodiment of the claimed invention, thecolor engine 550 or image processor 180 segments, breaks or divides theimage into a digestible format, e.g., four or more sections orquadrants. As exemplary shown in FIG. 9, the middleware engine 520stores ingested images from the outside feed, such as the IMS feed 505and/or the SCM feed 515, in the data warehouse 200 at step 1100. Thecolor engine 550 obtains stored image from the data warehouse 200 atstep 1110 and performs dynamic image analysis 560 to determine colors,preferably, dominant colors, of the image at step 1120.

The image segmentation processor 920 segments the retrieved image into aplurality of regions at step 1130 and the dominant color processor 930analyzes each region to generate a color histogram for each region atstep 1140. Typically, the size of images contained in Merchant's IMSdata feed 505 and/or Merchant's SCM data feed 515 are known. For unknownimage size, the middleware 520 or the image segmentation processor 920can modify or resize the image to a predetermined size, such as 500pixels by 500 pixels, thereby normalizing the image size for efficientand uniform image processing. As exemplary shown in FIG. 10, the imagesegmentation processor 920 can segment or divide the image into afour-quadrant grid, each grid subdivided into 16×16 cells, and analyzesthe subdivided image to determine the dominant color(s) and/orpattern(s) of the image. As each quadrant is analyzed, the dominantcolor processor 930 updates and reassess the resulting data to adjustits determination of the dominant color(s) and/or pattern(s) of thecolor swatch or image. From the color histogram, the dominant color 930generates a parseable, ordered list of colors ranking the most dominantcolors in each segment at step 1150.

In accordance with an exemplary embodiment of the claimed invention, theimage segmentation processor 920 may perform successive subdivisionssuch that a given cell or sub-image may be further divided or segmentedinto another grid, or another set of sub-images. Successivesegmentations of images may be necessary for the dominant colorprocessor 930 and/or pattern identification processor 940 to analyze andclassify complex patterns or images with various combinations of colorsand patterns. Preferably, the image segmentation processor 920 furthersegments the image by reducing the image segment height by half and/orthe image segment width by half if it cannot determine the dominantcolor within a predetermined threshold, e.g., 80% accuracy or certainty.Such determinations are made by determining and analyzing the frequency,quantity, and repeat of colors and/or patterns within the image by theimage analytics server 900. Accordingly, in addition to colordetermination, the image analytics processor 900 isolates, analyzes andidentifies patterns in the image, such as striped, plaid, paisley, polkadot, floral, etc. The divided parts/sections of the image are “read” andanalyzed by the image analytics server 900 to determine the dominantcolor(s) and pattern(s) appearing therein.

In accordance with an exemplary embodiment of the claimed invention, thedominant color processor 930 determines the dominant color byidentifying the color values across all pixels in each of the cells ofthe grid, including mean values and standard deviations. In a basicexample where an image or color swatch contains only one color and nopattern, the dominant color processor 930 identifies the image based onthe color appearing most frequently across all cells and assigns thehexadecimal value (and/or RGB values) associated with the identifiedcolor to the image. That is, the dominant color processor 930 comparesthe ordered lists of dominant colors and determines the most dominantcolor(s) within the entire image to be the color(s) that appear in themajority of segments with the highest frequency at step 1150. Thedominant color processor 930 associates and stores the dominant colorsdetermined for the product corresponding to the analyzed image and othercolor data, such as the ordered list of dominant colors in the datawarehouse 200 at step 1160. The image analytics server 900 dynamicallyconverts the determined dominant color(s) for the product image into theuniversal hexadecimal color language/system. It is appreciated that theclaimed system can also utilize other color models, such as HSV (hue,saturation, value), HSL (hue, saturation, lightness), CMYK (cyan,magenta, yellow key). The image analytics server 900 applies a curve tocolor histogram to allow for luminance variance in the extracted RGBcolors, e.g., 5-15% color variance along each of the bands whendetermining color dominance in a particular image. This allows for colorvariations in an image that are based on lighting conditions andshading, but not due to the presence of a different color in the image.Preferably, the dominant color processor 930 eliminates background noise(flat colors) that is not related to the object contained within theimage, such as white background. Of course, it should be understood thatthe dominant color processor 930 can utilize a similar process todetermine that multiple dominant colors are present in a single image,particularly when there are stark color contrasts in an image andincreased frequency of two or more distinct colors.

With respect to pattern recognition, the pattern identificationprocessor 940 analyzes the product image for any potential patterns whenthe dominant color processor 940 detects multiple dominant colors in theimage segment. The pattern matching process will be described hereinusing a basic plaid pattern as shown in FIG. 11a . Prior to assigning auniversal hexadecimal value to the pattern or its constituent colors,the pattern identification processor 940 compares and matches thepattern to a predefined set of patterns maintained in the core colordatabase 570. For example, the predefined set of patterns can includebut is not limited to plaid, striped, paisley, polka dot, floral, etc.The pattern identification processor 940 analyzes and processes productimages to associate the patterns to each product. Preferably, theclaimed invention incorporates sub-classifications of each of thepatterns to provide more robust classification. In this instance, a redand black plaid pattern is presented to the image analytics server 900for pattern and color determination. When analyzing the pattern, thepattern identification processor 940 determines the proximity andrepeated frequency of two or more colors. For example, where the firstcolor that is detected in a 3×3 pixel/unit square is next to anothercolor that is detected in a 3×3 pixel/unit square, then followed by thefirst color in the same configuration, the pattern identificationprocessor 550 determines and classifies the pattern as a plaid patternand assigns a “plaid” value to the image. After the pattern is definedand classified with a pattern value, the dominant color processor 930identifies the colors detected within in the pattern (in this case achecker pattern). Thereafter, the matched color processor of the colorsystem database server 950 assigns universal hexadecimal valuescorresponding to the dominant red and black colors appearing in theimage.

In accordance with an exemplary embodiment of the claimed invention, thepattern identification processor 940 can account for patterns that arerotated within the processed image, as shown in FIG. 11b . Even thoughthe border between the red and black colors is jagged when the image isprocessed, the pattern identification processor 940 processes theborders as a straight line with a 90 degree angle separating the edgesof the same color. With that information, as with FIG. 11a , the patternidentification processor 940 analyzes and determines that the imagepattern as a red and black plaid pattern by comparing the image patternto the pre-stored patterns in the color database 208.

In accordance with an exemplary embodiment of the claimed invention, thepattern identification processor 940 can account for patterns that aredistorted or stretched within the processed image. The patternidentification processor 940 divides the distorted image further intosmaller areas until it recognizes a pattern as being a red and blackplaid pattern by comparing the image pattern to the pre-stored patternsin the color database 208. The number of regions in the initial or laterdivision(s) may be based on the digital size of the image or swatch, ona defined quantity, historical analysis or another conventional basiswell known in the field of image recognition.

In accordance with an exemplary embodiment of the claimed invention, thecolor engine 550 or the image processor 180 performs successivesubdivisions of a given image or swatch to formulate a more preciserepresentation of the color and pattern values which are present in theimage. Without this process, an average color value of an entire imagestill can be determined. However, the color value associated with theimage would in many instances be an extremely poor representation of theactual colors in the image and of the product therein. For example,where a given image contains many different colors, the average colorvalue of the entire image may yield a grayish tone as opposed to variousdistinct colors that formulate the image. Thus, the color engine 550 orthe image processor 180 subdivides the image and analyzes eachsubdivided section independently from the others to capture the variousdominant colors of the image. In accordance with an exemplary embodimentof the claimed invention, the color engine 550 or the image processor180 subdivides the images into arrays of cells to accurately andprecisely represent the color values (e.g., color histogram and colorstatistics) of the image.

Turning now to FIGS. 8a-8g and 12, in accordance with an exemplaryembodiment of the claimed invention, the image processor 180 or thecolor engine 550 normalizes and codifies colors and patterns fromdigital photographic images or swatches of products received from theMerchant IMS 500 and/or the Merchant SCM system 510 into a universalcolor language/system, thereby enabling dynamic analysis of productsbased on colors and other parameters. The color engine 550 receives adigital photographic image or swatch of a shirt with patterns forprocessing and recognition at step 1000. The color engine 550 isolatesor extracts the relevant product pattern and color from the rest of theimage, with the irrelevant portion of the image being deemed backgroundor “whitespace” and discarded at step 1010. The color engine 550 scansthe image for proximity pixels at step 1020 and defines proximity pointsat step 1030. Once the proximity points are defined, at step 1040, thecolor engine 550 searches the image for a repeat pattern in theproduct-utilizing pattern repeat parameters defined in the colordatabase 208. Depending on the extent of pattern distortion of theproduct appearing in the image, as discussed herein with respect to FIG.11c , the color engine 550 further subdivides the image until it canidentify and determine the repeat pattern of the product.

In accordance with an exemplary embodiment of the claimed invention, thepattern identification processor 940 compares the repeat pattern to thepredefined set of patterns stored in the color database 208 to classifyor determine the product pattern. Once the pattern is classified, thedominant color processor 930 categorizes or determines the prevalent ordominant colors of the product at step 1050. The matched color processor960 codifies or converts the identified colors into the hexadecimalvalues of the universal color language/system and preferably, lists theidentified colors by its prevalence or frequency (i.e., the number oftimes a particular color appears in the product image), as exemplaryshown in FIG. 8g , at step 1060. For example, the dominant colorprocessor 930 and the matched color processor 960 can identify thefollowing five dominant colors represented by their universalhexadecimal values CB93B1, BDCADC, C3AECD, E3CFCD and EFEBE2. After allof these colors and the pattern are identified, the color engine 550associates the identified colors and/or patterns with this particularshirt and stores these codified color and pattern data as the productdata 206 in the data warehouse 200.

When analyzing patterns of multiple colors, the color engine 550identifies colors by sampling selected spots in a given region of theimage. When the sampling indicates that more than one color might exist,the color engine 550 further samples and/or further subdivides theimage, and may continue the process iteratively until only one color isidentified in the subdivision or the image subdivision is reduced to asingle pixel. In accordance with an exemplary embodiment of the claimedinvention, the image segmentation processor 920 selects the sizing orsubdivisions based on the number of colors identified in a region, thedeviation of values of the colors in a region (as compared to apredetermined threshold), or some other criteria. The dominant colorprocessor 930 analyzes each region's color values, for example on apixel-by-pixel basis. In addition, the image analytics server 900 storeseach sampled location of each region by its X, Y coordinates relative tothe entire image (together with its color values), and each region isassigned one or more color values based on the color determination.Further, the dominant color processor 930 instructs the color engine 550to search for pattern(s) in the image. The color engine 550 canrecognize a change in color when a certain parameter changes by morethan a fixed threshold, such as 15%. As a result, the color engine 550can built a virtual map which depicts colors in positions to indicatewhere color changes occur and, in aggregate, a pattern can emerge. Byidentifying each region's color and the location of each region relativeto the entire image, the color engine 550 can determine patterns, forexample, using pixel geometry techniques that are known in the art. Oncethe patterns and colors are determined, the color engine 550 assignsidentifying numerical values. Preferably, the color engine 550 providesa lesser weight to background colors of white or black.

Once the color data for the color swatch, in accordance with anexemplary embodiment of the claimed invention, the color engine 550 orthe image processor 180 associates or maps the color swatch to one ofthe 4096 universal hexadecimal codes based on Euclidian distance betweenthe determined color of the image and the claimed universal colorlanguage/system. The determined value of the image is compared to all ofthe values of the universal color language/system to reverse map thecolor (e.g., the Merchant's product color). Preferably, the color engine550 or the image processor 180 compares the determined value to each ofthe 4096 hexadecimal colors/values/codes of the claimed universal colorlanguage/system and determines the Euclidian distance between thedetermined value of the image and each hexadecimal code. The matchedcolor processor 960 of the color system database server 950 assigns theimage the hexadecimal code yielding the lowest Euclidean distance andassociates the hexadecimal value and the corresponding Euclideandistance with the image in the data warehouse 200.

Where the determined color from the image analysis 560 is not preciselythe same as one of the universal colors (i.e., one of the 4096 colors)in the color database 208, the matched color processor 960 selects acandidate color that is the closest one of the available colors in thecolor database 208. In accordance with an exemplary embodiment of theclaimed invention, the matched color processor 960 determines thecandidate color by using the following formulac=sqrt((r−r₁)²+(g−g₁)²+(b−b₁)²), wherein c=closest color; r=first redvalue; r₁=second red value; g=first green value; g₁=second green value;and b=first blue value b₁=second blue value. Using component RGB valuesfor the candidate colors and known color from the processed image, theclosest candidate color to the known color present in the processedproduct image is the color that yields a value where c is closest to 0.(A value of c=0 means that the colors are the same.)

Once a candidate color is selected as a result of the image analysis560, the color engine 550 generates a record in a color-pattern table580 at step 1070 which utilizes a unique item or product ID of theproduct listed in the item table 540 to link a given product provided bythe IMS feed 505 and/or the SCM feed 515 to the hexadecimal code of thecandidate color in the color pattern-table 580. That is, the colorengine 550 syncs the normalized and converted color data of the IMS datafeeds 505 and/or the SCM data feeds 515 into the universal hexadecimalcolor codes, thereby establishing a universal color code or identifierfor each product that was input into the server 100 from the Merchants'IMS 500 and/or the Merchants' SCM systems 510. The productcategorization engine 190 determines a product category of the productassociated with the normalized and color categorized/converted productdata (i.e., color analyzed product) and categorizes the color analyzedproduct into the determined product category at step 565. Thisadvantageously enables the claim system to normalize, categorize,codify, search and dynamically analyze products from a plurality ofMerchants by color rather than by text. That is, the claimed inventionreverse maps various Merchant color systems into one universal colorlanguage/system.

In accordance with an exemplary embodiment of the claimed invention, theimage processor 180 or the color engine 550 reverse maps the current andnon-uniform color conventions and identifications of Merchants withoutfundamentally damaging or totally eliminating those Merchants' owncolor-naming preferences. The matched color processor 960 converts theRGB value to the closest matching hexadecimal value within the universalcolor language/system to reverse map the Merchant's product colors tothe universal hexadecimal codes of the claimed invention. In accordancewith an exemplary embodiment of the claimed invention, the imageprocessor 180 or the color engine 550 converts using a proximitynumerical search to locate a single color in the universal colorlanguage/system that most closely matches the three RGB values of theimage. In addition to the claimed color classification of identifyingcolors by hexadecimal or RGB codes, e.g., hexadecimal code FF0066corresponding to the RGB code (255 Red, 0 Green, 102 Blue), the colormay also be identified in the data warehouse 200 and/or Merchantdatabase using the Merchant's unique color name or alias, e.g.,“flamingo pink.” Likewise, other Merchants that wish to assign their ownalias to that very same color may do so using a different name.Regardless of the number of aliases applied to the particular color, thekey is that all are codified and searchable using the standardizedhexadecimal and/or RGB values assigned to the color.

By reverse mapping all major Merchants' color systems into a singleuniversal color language/system, a significant hindrance to usersearching for and finding products from different Merchants is resolved.Reverse mapping enables dynamic analysis and codification of precisecolor. When layered into proprietary Merchants' IMS 500 and/orMerchants' SCM systems 510, the search is further enhanced as it is nolonger requires scraping the Internet. Likewise, issues associated withMerchant product planning and production is ameliorated by providingthem with standardized color information on sales, searches andavailability.

Following the consumption of normalized and categorized data from theISM data feeds 505 and/or the SCM data feed 515, and color assignmentutilizing universal hexadecimal color identifiers, as exemplary shown inFIG. 7, a number of Merchant tools are enabled which pertain topredictive analytics 610, a B2C platform which includes a digitalpersonal shopper application 620, advertising to consumers 630 and otherapplications 640. Notably, these tools leverage the ability of thesystem to capture codified color data from a plurality of customizedproprietary IMS and SCM systems 500, 510 previously unavailable in theprior art.

Upon following an acceptable format and input of information, the SCMdata feeds 510 are transmitted and loaded onto server 100 by theMerchant's SCM system 510 as soon as the product goes into production.As products are manufactured and are ready to enter inventory, thedatabases in the Merchant's SCM systems 510 and/or the Merchant's IMS500 are updated to reflect available inventory of product, resulting inadditional data being sent from the SCM systems 510 and/or IMS 500 tothe server 100. In accordance with an exemplary embodiment of theclaimed invention, once products enter Merchant inventory, events aretriggered to issue and release targeted advertisements, digitalcatalogues and other marketing tools to connect now-available productswith consumer users. Where there are delays in production of product ofa certain color, the SCM feeds 515 and/or the IMS feeds 505 are likewiseupdated, which may trigger other advertising events. As availableproducts are sold, the IMS 500 continue to be updated, withcorresponding data being sent to the server 100. While the exampleherein references information initially input and fed to server 100 viathe supply chain, it should be appreciated that information may be fedto server 100 utilizing inventory management information that typicallyrelates to the post-production status of product.

In the examples presented above, colors are determined and classified in6-digit hexadecimal values or hexadecimal code. However, it should beunderstood that the available colors for classification can be adjustedto correspond to an expandable or fixed color environment. For example,in an expandable environment of colors, a color in a given image isassigned a 6-digit hexadecimal value (and corresponding RGB values) thatcorresponds to one of the 4,096 selectable values but can expand toinclude additional colors as needed. The assignment of the 6-digithexadecimal value (and corresponding RGB values) enables expansion ifadditional colors are desired beyond 4,096 through the 16+ millioncolors that are actually available. It should be appreciated that eachhexadecimal code can be converted into component RGB values and/or abinary representation.

In a fixed environment of 4,096 colors, each of the component RGB colorspresented on a scale of 0 to 255 can be adjusted downward to 16intensities of RGB, respectively, on a scale of 0-15. Based on the 16color intensities of each of these colors, a total of 16³ or 4096 colorsvariations are possible. For example, the color identified inhexadecimal code as CB93B1 and corresponding RGB values: 203 Red: 147Green: 177 Blue could be adjusted on a 4096 color scale to hexadecimalcode C9B and corresponding RGB values: 13 Red: 9 Green: 11 Blue, byusing the closest values on the 16-level RGB scale. On this form ofscale, these values would be associated with a product, such as a shirt,to which the image or color swatch belongs such that when a query forcolor C9B is made, one of the recommendations and or product results isthe shirt. While utilizing only 16 RGB intensities (and 3 hexadecimaldigits) does not easily lend itself to color expansion, it still permitsa fair level of color variance sufficient for consumer and Merchantclassification. The full 4096 hexadecimal codes of the claimed inventionis more fully set forth and described in applicant's co-pendingapplication Ser. No. 13/762,160 and PCT/US123/25135 (hereinafter“applicant's '160 application”), each of which is incorporated herein byreference in its entirety.

All user subscribers (e.g., Merchant users, consumer users, etc.) gainentry and access to the server 100 by subscription and by using knownsecurity approaches, such as a login and password, which are optionallymanaged by a separate login server (not shown). Once a login isconfirmed and a subscriber is authenticated, the processor 110 of theserver 100 loads a user's age, gender, location and other demographicinformation from the user database 202. The color search engine 120 ofthe server 100 provides the verified consumer user access to the searchquery functions 730 via a graphical user interface (GUI) 700 and theprocessor 110 of the server 100 provides the verified Merchant user withaccess to additional data available to them under its subscription.Unlike the consumer user/subscriber, the Merchant user/subscriber cansearch the SCM systems 510 to determine the production status/scheduleof a particular product and/or to examine/verify the color andspecification of the components of the product before moving forwardwith the production of the product.

For an unauthorized user or non-licensee of the service provider, whenthe client device 300 associated with the unauthorized user (i.e.,non-subscriber) attempts to access the server 100, in accordance with anexemplary embodiment of the claimed invention, the processor 110 deniesthe client device 300 access to the server 100 and transmits aregistration webpage to the client device 300 so the user can subscribeto the services provided by the service provider and become aregistered/authenticated subscriber using any known methods. Aftercompleting the registration process, the user has an option ofdownloading a mobile search application onto her client device 300 toseamlessly and/or automatically connect to the service provider's server100. In addition or alternatively, the server 100 may permit the clientdevice 300 of the unauthorized user to perform at least one color basedsearch as a teaser to encourage the unauthorized user to become asubscriber and subscribe to the service provider's services.

As shown in FIGS. 13 and 14, more fully described in applicant'sco-pending U.S. application Ser. No. 14/055,884 and internationalApplication No. PCT/US13/65333 (hereinafter “applicant's '884application”), the user initiates a color-based search query using theGUI 700 of the color search engine 120 display on the client device 300associated with the user. By selecting a selectable color area or swatch702 of the GUI 700, as exemplary shown in FIG. 4, a user initiates asearch for products from the data warehouse 200 and/or Merchants' IMS500 and/or Merchants' SCM systems 510 (collectively and interchangeablyreferred to herein as the “database engine 250”) with the associateddigital color codes (e.g., in hexadecimal, RGB, binary) that correspondto the selectable color swatch 702. It should be appreciated that thequery or queries sent to the data warehouse 200, to the IMS 500 and tothe SCM systems 510 (the database engine 250) is referred to herein as asingle query for ease of reference. As exemplary shown in FIGS. 3A-3B,13 and 14, when a user desires to search for products of a particularcolor, the user selects a color from one of the selectable color barcolors that appear on the clickable horizontal color bar 703. Once oneof the colors on the horizontal bar 703 is selected, a vertical bar 704expands downward, typically with shades of the initial color selected onthe horizontal color bar 703. Once a user makes a final color selection,which make include one or more colors, the client device 300 transmits acolor search criteria 730, 2400 to the color search engine 120 of theserver 100 over the communications network 400. The color search engine120 searches the database engine 250 for products matching or closest tothe user's final color selection. That is, the color search engine 120sends the color search criteria 730, 2400 in a query to the databaseengine 250. It is appreciated that each IMS 500 is associated with adifferent merchant, retailer, wholesaler, manufacturer and the like, andeach SCM system 510 is associated with a different merchant, retailer,wholesaler, manufacturer and the like. It is appreciated that theproducts can be any goods, including but not limited to apparel, shoes,hats, ties, socks, scarves, fashion accessories, home furnishings,furniture, appliances, bicycles, cars, paints, lipsticks, hair dyes,make-ups, nail polishes and any other product in which is a component.

In accordance with an exemplary embodiment of the claimed invention, thecolor search engine 120 searches the database engine 250 for productsthat meet the color search criteria 730, 2400, i.e., the associateddigital color code(s) corresponding to the selected color swatch(es)702. The color search engine 120 transmits the search results 740, 2420containing information about the products matching the user's colorsearch criteria 730, 2400 to the client device 300 associated with theuser over the communications network. The color search engine 120 storesthe color search criteria 730, 2400 and the search results 740, 2420 inthe data warehouse 200. Preferably, the color search engine 120 updatesthe user color preference history 2430 based on the user's color searchcriteria 730, 2400.

However, if no product matching the user's color search criteria 730,2400 is found in the data warehouse 200, the color search engine 120searches one or more IMS 500. Preferably, the color search engine 120transmits a single query comprising the user's color search criteria730, 2400 to both the data warehouse 200 and the IMS 500 to search bothof them simultaneously. If no product matching the user's color searchcriteria 730, 2400 is found in the data warehouse 200 and the IMS 500,then the color search engine 120 searches the SCM systems 510 todetermine if any product matching the user's color search criteria 730,2400 is in the “supply chain” or the “pipeline” (i.e., the matchingproduct is currently being shipped, manufactured, etc.). The colorsearch engine 120 transmits the search results 740, 2420 comprisingfuture inventory information, e.g., product availability information, tothe client device 300 associated with the user over the communicationsnetwork 400.

In accordance with an exemplary embodiment of the claimed invention, ifno product matching the user's color search criteria 730, 2400 is found,then the color search engine 120 returns search results 740, 2420comprising product(s) with nearly the same or closest color to thequeried color of the user's color search criteria 730, 2400. That is,the color search engine 120 returns product with the hexadecimal code ofthe universal color language/system that is nearly the same or closestto the hexadecimal code of the queried color of the user's color searchcriteria 730, 2400. In accordance with the exemplary embodiment of theclaimed invention, color search engine 120 of the server 100 executesthe following exemplary calculation to determine the closest matchingcolor to the queried color: c=sqrt((r−r₁)²+(g−g₁)²+(b−b₁)²), whereinc=closest color; r=red value of the queried color; r₁=red value of thecandidate color; g=green value of the queried color; g₁=green value ofthe candidate color; and b=blue value of the queried color; and b₁=bluevalue of the candidate color. The candidate matching color is the one ormore colors that yield the value closest to zero.

Preferences in the color swatches 702 appearing on the color bars 703,704 may also be controlled and modified via the GUI 700, such as byutilizing the bookmark feature 707. In controlling changes to selectablecolors that readily appear on the color bar display 2610 of the GUI 700,the color search engine 120 generates user-specific color bar display2610 or 2620 based on the user color history, user's purchase history,user's search history and the like. That is, the color search engine 120displays GUI 700 with the personalized color bar display 2620 instead ofthe normalized color bar display 2610 on the client device 300associated with the user after acquiring sufficient data to determineuser's color preferences. Alternatively, the color search engine 120displays the personalized color bar display 2620 when the user clicks onthe more button on the normalized color bar display 2610. The userselects one or more colors on the normalized color bar display 2610 orthe personalized color display 2620 to search for products in thedatabase engine 250.

In accordance with an exemplary embodiment of the claimed invention, theGUI 700 additionally comprises a textual search field 705 for user toenter additional optional search parameters 2410, such as patterninformation, e.g., plaid, and textual search criteria, e.g., size,brand, Merchant, polo shirt, paint, blender, nail polish, etc. The colorsearch engine 120 searches the database engine 250 for products thatmeet both the textual search criteria 2410 and color search criteria2400 (i.e., the associated digital color codes (e.g., in hexadecimal,RGB, binary) that correspond to the selected color swatch 702. If noadditional search parameters 2410 are provided by the client device 300,then the color search engine 120 searches the database engine 250 forproducts that meet only the color search criteria 2400, i.e., theassociated digital color code(s) corresponding to the selected colorswatch(es) 702.

When additional search parameters 2410, such as “Polo Shirt” arereceived from the client device 300 over the communications network 400,in accordance with an exemplary embodiment of the claimed invention, thecolor search engine 120 provides search results 2420 with products oritems from the database engine 250 that meet both the color searchcriteria 2400 and textual search criteria 2410: a) the hexadecimal colorcode(s) of the selected color swatch(es) of the color search criteria2400, e.g., hexadecimal code 9CAED4 as exemplary shown in FIG. 4; and b)the textual search parameter or criteria 2410, e.g., “Polo Shirt” asexemplary shown in FIG. 4. The color search engine 120 transmits thesearch results 2420 returned by the database engine 250 to the clientdevice 300 over the communications network 400. The client device 300renders the search results 2420 in a display area 706, as exemplaryshown in FIG. 4. Although only eight products are shown in the displayarea 706 in FIG. 4, additional products of the search results 2420 canbe displayed or brought into the display area 706 by using any knowmethods, e.g., using a slider on the screen or GUI 700.

In addition to receiving results 2420, in accordance with an exemplaryembodiment of the claimed invention, the system further provides a userwith a number of user actions or options 800 to share the product via asocial medium 810 (and to a social database 812), to “like” the product820, to save the product as a bookmark 830 or into a user registry, to“hide” the product to ensure that it never appears again in a user'ssearch results 840, and to purchase the product 850. When selections aremade, they are stored as records in a user history table 860 andconveyed to the real-time analytics processor 170 of the server 100 toanalyze and utilize for future recommendations to the user and to otherswith correlating selections and/or demographics. Thus, information fromsearches performed by users of available products or merchant inventoryis organized and indexed as user data and is used to formulate userpreferences that is available to be used for future recommendations tothe users providing the data, as well as to other users sharing commonuser demographics and/or online shopping activities.

In accordance with an exemplary embodiment of the claimed invention,when resources permit, the color search engine 120 queries the databaseengine 250 continuously and automatically for products with identifyingcolors that match those colors appearing as selectable color swatches702 on the user's personalized color bar display 2620. The color searchengine 120 receives the search results 2420 from the database engine 250and transmits the search results 2420 to the client device 300associated with the user over the communications network 400. The clientdevice 300 populates the display area 706 with the products/items of thesearch results 2420 before the user initiates a formal search.Preferably, the search results 2420 comprises products/items from theIMS 500 so that the products/items shown in the display area 706 areproducts/items that are currently available and in stock.

In accordance with an exemplary embodiment of the claimed invention, theuser can input additional color search criteria 2400 and/or additionaltextual search criteria 2410 into the GUI 700 so the color search engine120 can narrow or filter the search results 2420, for example, to findspecific types of products that are currently available for purchasefrom Merchants within the user's current geo-location. These additionalparameters or criteria may include, but is not limited to, a second orthird color swatch or hexadecimal code, a specific pattern, or aphysical attribute, such as size.

In accordance with an exemplary embodiment of the claimed invention, theuser can select one or more of the products displayed on the displayarea 706 for purchase. The client device 300 transmits a purchaserequest to the server 100 over the communications network 400 when theuser selects a product to purchase from the display area 706. Theprocessor 110 may utilize the user's shipping and billing informationstored in the user database 202 to process the user's purchase of theproduct. In addition or alternatively, the processor 110 may lead theuser through a series of GUIs displayed on the client device 300 toinput the required billing and shipping information to complete thepurchase. The GUIs can be either linked through the provider's server100 or through a Merchant's website.

In accordance with an exemplary embodiment of the claimed invention, theprocessor 110 stores the purchased products/items 2330 as purchaserecords in the user database 202 and stores de-personalized purchasedinformation in the product database 206, e.g., user's gender anddemographic information. The real-time analytics processor 170 mayutilize such de-personalized information to determine a common ortypical profile of users purchasing such a product or to determine colortrends based on gender, age, geo-location and the like. If the purchasedproduct is on the user's wish list 2320, then the user module 150removes or deletes the purchased product from the user's list so thatthe members of her approved social group 2360 is made aware that an itemhas been purchased from the user's wish list 2320, thereby decreasingthe likelihood of duplicate purchases. Alternatively, the user module150 may hide the gift purchases from a user's wish list 2320 from theowner of the wish list 2320 to keep any gift purchases secret from theowner.

In accordance with an exemplary embodiment of the claimed invention, thereal-time analytics processor 170 couples the demographic data withother data such as, but not limited to, a user's purchase and shoppinghistory, as well as data regarding industry trends and consumer colorpreferences, so as to algorithmically recommend colors and products toboth users and Merchants.

While the embodiments illustrated herein enable a user to search for aplurality of desired colors in one item (e.g., a first color and asecondary color), as well as specific pattern-color combinations (e.g.,blue and red plaid), the color search engine 120 can perform othercomparable searches on the database engine 250. In accordance with anexemplary embodiment of the claimed invention, the color search engine120 searches for “complementary” colored items to a queried color orcolor search criteria 2400. Each selectable color swatch 702 in thecolor bar display 2610 and the personalized color bar display 2620 isnot only associated with a unique hexadecimal code of the universalcolor language/system but also is associated with hexadecimal code(s) ofone or more complimentary colors. Accordingly, when the user selects toinclude the complementary color search as additional search parameter orcriteria 2410 in her search for products, the color search engine 120searches the database engine 250 for product/items that meet the user'squeried color of the color search criteria 2400 and the complementarycolors associated with the user's queried color. That is, the searchresults 2420 comprises a list or set of products/items satisfying thecolor search criteria 2400 and/or additional textual search criteria2410, and a list of set of product/items satisfying one or morecomplementary colors associated with the user's queried color. Forexample, a given shade of blue complements or “go with” all other shadesof blue along with a small sample of shades of red, then the searchresults 2420 may additionally comprise lists of products/itemssatisfying the complimentary shades of blue and red accordingly. Thecolor search engine 120 transmits the search results 2420 comprisinglists or sets of products satisfying the color search criteria 2400 andthe complementary colors associated with the queried color to the clientdevice 300 over the communications network 400. In accordance with anexemplary embodiment of the claimed invention, the color search engine120 selects the complementary colors that are within a predeterminedrange of the hexadecimal color code of the queried color 2400.

In addition or alternatively, the user may select to include thecomplementary colored item search as additional search criteria 2410 inher search for products. The color search engine 120 searches thedatabase engine 250 for product/item to accompany a certain color item.For example, the user may use the color search engine 120 to search forshoes that are complementary to an “olive green” jacket or for curtainsthat are complementary to a blue and white floral patterned sofa.

In addition to providing the search results 2420, in accordance with anexemplary embodiment of the claimed invention, the processor 110 furtherprovides a user with a number of user actions or options to share theproduct/item on the search results 2420 with user's approved socialgroup 2360, to add the product/item to the user's wish list 2320, to addthe product/item to the user's bookmark 2340, to add the product/item tothe user's deleted list 2350 so that the deleted product/item will notbe included in any future user's search results 2420, and to purchasethe product/item. When selections are made by the user, the color searchengine 120 stores the user's selections as records in the user database202. That is, the color search engine 120 stores the sharedproducts/items as social registry records, wish list products/items aswish list records, bookmarked products/items as bookmark records,deleted product/items as deleted records and purchased product/items2330 as purchase records in the user database 202. Additionally, thecolor search engine 120 conveys the user's selections or records to thereal-time analytics processor 170 of the server 100 for processing andanalysis. The product recommendation engine 160 utilizes the analyzeddata for future recommendations to the user and to others withcorrelating selections and/or demographics. Thus, information fromsearches performed by users of available products or Merchant inventoryis organized and indexed as user data and is used to formulate userpreferences that is available to be used for future recommendations tothe users providing the data, as well as to other users sharing commonuser demographics and/or online shopping activities.

In accordance with an exemplary embodiment of the claimed invention, thecolor search engine 120 performs product/items searches using the colorand/or pattern preferences of the user stored in the user database 202.The user module 150 updates the user's color and pattern preferences(collectively referred to herein as the “user color or preferencehistory 2430”) based on one or more of the following: the user's searchcriteria 2400, 2410; and user's selection of a particular product/itemto share with user's approved social group 2360, to add to user's wishlist 2320, to add to the user's bookmark 2340, or to purchase.Preferably, the user module 150 categorizes user color preferencehistory by product type, e.g., fashion, home, etc., as exemplary shownin FIG. 15.

In accordance with an exemplary embodiment of the claimed invention, asexemplary shown in FIGS. 13 and 14, when the client device 300associated with the subscriber (i.e., a registered user) access theserver 100, the processor 100 transmits an application page or GUI 2300to the client device 300. The client device 300 displays the applicationpage 2300 comprising the subscriber's or primary user registry GUI 2310.In accordance with an exemplary embodiment of the claimed invention, theprimary user registry GUI 2310 comprises one or more following exemplaryselectable or clickable GUIs displaying: product/items on the user'swish list 2320, the purchase list 2330 of the products/items purchasedby the user, products/items on the user's bookmark 2340, products/itemson the user's deleted list 2350, user's approved social groups 2360,user's favorite stores list 2341 and user's favorite brands list 2342.When the user clicks or selects the approved social group GUI 2360, theprocessor 110 displays expanded GUI 2365 with photos or identifier(e.g., username, nick name, etc.) of various members of the user'sapproved social group/registries.

In accordance with an exemplary embodiment of the claimed invention, asexemplary shown in FIG. 13, the color search engine 120 automaticallyperforms default searches for products based user color preferencehistory 2430 and/or the user's personalized color bar display 2620,preferably each time the user color preference history 2430 and/oruser's personalized color bar display 2620 is updated. When the clientdevice 300 associated with the subscriber access the GUI 700 to initiatea color-based search query, the color based engine 120 transmits thesearch results 2420 returned by the database engine 250 in response tothe default search to the client device 300 over the communicationsnetwork 400. The client device 300 renders the received search results2420 in the display area 706, as exemplary shown in FIG. 14.

In accordance with an exemplary embodiment of the claimed invention, asexemplary shown in FIG. 13, the color search engine 120 automaticallyperforms default searches for products based on each approved socialgroup member's color preference history 2440 and/or each member'spersonalized color bar display 2620, preferably each time the member'scolor preference history 2440 and/or member's personalized color bardisplay 2620 is updated. When the client device 300 associated with thesubscriber access the GUI 700 to initiate a color-based search query fora member of the user's approved social group 2360 (i.e., a secondaryuser), the color based engine 120 transmits the search results 2420returned by the database engine 250 in response to the default searchfor the secondary user to the client device 300 over the communicationsnetwork 400. The client device 300 renders the received search results2420 in the display area 706, as exemplary shown in FIG. 14.

In accordance with an exemplary embodiment of the claimed invention, thecolor search engine 120 ranks the search results 2420 or arranges thesearch results 2420 in an ordered list from most relevant to leastrelevant, e.g., the products/items with color hexadecimal code closer tothe queried color is considered more relevant and is presented higher inthe search result ordering. The color search engine 120 transmits theranked or ordered search results 2420 to the client device 300 over thecommunications network 400 such that the client device 300 displays thesearch results 2420 in the display area 706 from most relevant to leastrelevant. In addition or alternatively, the color search engine 120 mayconsider other factors, such as user preference, product availability,Merchant or user ratings, in determining the ordered search results2420, i.e., relevancy of the products/items on the search results 2420.

In accordance with an exemplary embodiment of the claimed invention, theuser may view, rate, store, purchase, or discard the products/items onsearch results 2420 displayed on the display area 706 of the clientdevice 300. The user module 150 maintains a browsing history for eachuser in the user database 202 and adds/keeps a product/item viewed bythe user in the user's browsing history. That is, for example, if theuser views a product in the user's search results 2420, the user module150 adds the product to a listing of the user's browsing history storedin the user database 202. It is appreciated that the user make changesto her stored browsing history at any time. For example, if an item isof no interest to the user, the user may delete that item from herbrowsing history. In accordance with an exemplary embodiment of theclaimed invention, a user may specify that a particular search ispersonal, the color search engine 120 will not make such search result2420 available to anyone other than the user. That is, the color searchengine 120 does not make that particular search result 2420 available tothe user's approved social group 2360. If the user's search for productis for another person, e.g., a gift search for her spouse, the colorsearch engine 120 may not make the search results 2420 available to herspouse, but may make it available to other members of the approvedsocial group 2360. The user module 150 segments out the browsinginformation from the user's browsing history for any searches made foranother person by the user to provide a more accurate user-specificbrowsing information.

In accordance with an exemplary embodiment of the claimed invention, auser may rate the products to indicate a level of interest (e.g., of nointerest, of little interest, of great interest). The processor 110 orthe user module 150 stores the user rating, whether it be according to aphrase (e.g., “of no interest”), or according to a numerical scale, as anumerical value associated with that product in the product database206. The product recommendation engine 160 may utilize the user ratinginformation to recommend products to members of the user's preapprovedsocial group 2360 or other users of the claimed system.

If a user wants to delete any rating or does not want the processor 110to store a viewed product in a browsing history stored in the userdatabase 202, the user may select to discard any data associated withthe viewed product. Should a user select to discard any data associatedwith the viewed product, the processor 110 or the user module 150 willeither store no data or delete any data stored associated with theviewed product from the user database 202 or it will be stored that theuser selected to delete the product from her profile.

In accordance with an exemplary embodiment of the claimed invention, theuser can add one or more of the products displayed on the display area706 to the user registry 2310, e.g., to the user's wish list 2320, or tothe registry 2310 of a member of user's approved social group 2360. Theregistry module 140 allows a user to store, share, and edit a listing ofproducts, such as a wish list 2320 or other registry of products. A usermay select to save a selected product to a listing of products, such asa wish list 2320. A user and her members of her approved social group2360, if permission is granted by the user, can view any saved listingby accessing the registry module 140 over the communications network 400using her client device 300.

The client device 300 transmits a registry add request to the server 100over the communications network 400 when the user selects a product toadd to her registry 2310 from the display area 706. The registry module140 adds the selected product to the user's registry 2310 stored in theuser database 202 or to the registry 2310 of a member of the user'sapproved social group 2360. The registry module 140 further storesde-personalized product registry information in the product database206, e.g., gender and demographic information of user showing interestin a product. The real-time analytics processor 170 may utilize suchde-personalized information to determine a common or typical profile ofusers showing an interest in such a product.

In accordance with an exemplary embodiment of the claimed invention, theregistry module 140 allows a user to share with another user (e.g.,members of her approved social groups 2360) all or partial informationstored for that user in the user database 202. Amount of information tobe shared with members of her approved social groups 2360 can vary bygroup, e.g., user may elect to share more information with a group ofher friends than a group of her work colleagues. The user may wish toshare some of her user data (e.g., name, birthday, demographic data, andcolor preference information) with members of her approved social group2360. This will allow any members of her approved social group 2360 tonot only see the saved listings of products, but also any otherinformation selected by the user to share with her approved social group2360, such as user's browsing history, product ratings, calendar, colorpreferences, personal information, favorite brands list 2342, favoritestore list 2341, etc. In this manner, members of the user's social group2360 may see that a certain event, such as the user's birthday oranniversary, is occurring and may view her wish list 2320 to purchase anappropriate gift for the user.

In accordance with an exemplary embodiment of the claimed invention, afirst user may request to share specified information with that seconduser. Once a second user accepts that request, the first user and thesecond user may share all or parts of their user data, product dataand/or color data stored in the data warehouse 200 with each other andeach may associate that second user with a certain contact grouping2360. By way of example, a contact grouping may be friends, family,romance, work, etc. The registry module 140 stores each accepted requestand associated contact grouping or social group 2360 in the userdatabase 202 and links the social group to the stored user data.

As exemplary shown in FIG. 13, the registry module 140 provides ordisplays the user profile information, social groups 2360, wish list2320, purchase list 2330, bookmarks 2340, browsing history, etc. forviewing by the user on the application page 2300 displayed on the clientdevice 300. The processor 110 transmits a primary user registry GUI 2310to be displayed within the application page or GUI 2300 to the clientdevice 300 over the communications network 400. The primary userregistry GUI 2310 allows a user to access the registry module 140 tobrowse her contact or social groups 2360, to examine other userinformation, such as birthday information, and to shop for items thatanother user in the approved social group 2360 has posted on her wishlist, browsing history, or purchase history. Furthermore, because theprofile information of other users is available, the registry module 140allows the user to set reminders for other users in the social group2360, such as a birthday or other event reminders.

In accordance with an exemplary embodiment of the claimed invention, theuser module 150 and/or registry module 140 present various GUIs on theclient device 300 for the user to enter information regarding the user(such as birth date) and to identify affinity or social groups 2360 andmembers of affinity groups (such as friends, family, etc.) The user datamay include a photograph and any user input for creating a user profileand/or color profile, and is stored in the user database 202. Theregistry module 140 may display a sliding GUI 2365 of people in theuser's affinity or social group 2360 with photos or identifier (e.g.,username, nick name, color preferences, etc.). In accordance with anexemplary aspect of the claimed invention, when the primary user clickson the photo or identifier of a member of user's social group 2360,e.g., user 3 displayed on the sliding GUI 2365 in FIG. 13, the registrymodule 140 connects the primary user's client device 300 with the clientdevice 300 of the user 3 over the communications network 400 so that theprimary user can communicate with user 3 via text, email, voice and/orvideo.

In accordance with an exemplary embodiment of the claimed invention, theuser module 150 stores user's calendar as user data in the user database202, as well as events, e.g., birthday, anniversary, etc., andreminders. The user module 140 enables the user to connect past eventinformation to her profile. The registry module 140 may link the pastevent information to user data stored in the user database 202,including event descriptions, event date information, event photographs,and event videos, such that other users who are connected to that usermay view the event.

In accordance with an exemplary embodiment of the claimed invention, asexemplary shown in FIGS. 16-18, the claimed invention may be utilizedfor quality control, e.g., to ensure that manufacturer has produced thegoods in correct color. That is, as exemplary shown in FIG. 17, theclient device 300 associated with the Merchant user transmits a colordigital image 2500 of the product, e.g., a green shirt supposedly havingthe universal color code “11ff66,” to the server 100 for verification orquality control over the communication network 400. The Merchant userutilizes its client device 300, such as a web enabled device 300, e.g.,a smart phone 300 with a built-in camera 310, a tablet 300 with abuilt-in camera 310, a laptop 300 with a built-in camera 310, etc., toobtain a photo or digital image 2500 of a product/item and stores thecaptured image in the memory 330 of the client device 300. In additionor alternatively, the client device 300 may receive the digital image2500 via email text, and the like, or retrieve the image 2500 from thememory 330 of the client device 300.

In accordance with an exemplary embodiment of the claimed invention, theprocessor 320 of the client device 300 normalizes and codifies colorsfrom one or more digital images 2500 of the product/item selected by theuser into the universal color language/system. The client device 300transmits the universal color code(s) associated with the digital image2500 to the server over the communications network 400 via the networkconnection facility 350. As described more fully in applicant'snormalization/codification application and as exemplary shown in FIGS.8a-8g and 12, in accordance with an exemplary embodiment of the claimedinvention, the processor 320 of the client device 300 performs a“mobile” or “light” version of the full normalization process 2630performed by the server 100. In addition or alternatively, the processor320 of the client device 300 may perform none of the normalizationprocess 2630 and rely entirely on the server 100. That is, the clientdevice 300 may transmit the digital image 2500 to server 100 to identifythe dominant colors. It is appreciated that this does not necessarilypreclude the client device 300 with a more powerful processor 320 and alarger memory 330 from performing the full normalization process 2630 aspreformed by the server 100.

In accordance with an exemplary embodiment of the claimed invention, asexemplary shown FIGS. 8a-8g , 12 and 16-18, the processor 320 of theclient device 300 or the image processor 180 of the server 100 receivesa digital image 2500 of a shirt with patterns for processing andrecognition at step 1000. In the full normalization process 2630, theimage processor 180 performs the steps 1010-1070. For the mobilenormalization process, the processor 320 or image processor 180 skipsthe steps 1020-1040 shown in FIG. 12. Since both the mobilenormalization and full normalization process 2630 has already beendescribed herein, the discussion will not be repeated here.

After the colors have been identified, the processor 320 or the imageprocessor 180 associates the identified colors with this particulardigital image 2500 and stores these codified color data in the memory330 or the data warehouse 200 at step 1070. In the case where the mobilenormalization process is performed by the processor 320, the clientdevice 300 transmits the codified color data of the digital image 2500(i.e., the identified hexadecimal color code(s) associated with thedigital image 2500) to the server 100 over the communications network400 via the network connection facility 350 for analysis and processing2510.

For an authorized Merchant user or licensee of the service provider, theuser has access to the normalized or personalized color bar display2610, 2620 on its client device 100 to select the color(s) 702, 703 ofthe product/item ordered from the manufacturer, e.g., a green shirthaving the universal color code “11ff66” in this hypothetical example.The selection of colors for quality control by the Merchant user issimilar to the selection of colors by the consumer/Merchant user forinitiating color-based search query as described herein. The clientdevice 300 transmits the color code “11ff66” of the product/item orderedor to be produced/manufactured by the manufacturer to the server 100over the communications network 400. The server processor 110compares/analyzes the universal color code of the digital image 2500(i.e., the color of the manufactured item) received from the clientdevice 300 or determined by the image processor 180 to the universalcolor code associated with the color of the ordered product/itemreceived from the client device 300. The server processor 110 eitherdetermines whether the universal color code of the digital image 2500 ofthe manufactured product/item matches or is within a predeterminedparameters or threshold 2520, which may be established by the Merchantor the service provider, of the universal color code of the orderedproduct/item. That is, the server processor 110 determines if the colorof the manufactured product/item matches or is within the predeterminedrange or threshold of the color of the ordered item. The serverprocessor 110 transmits an accept message to the client device 300 overthe communications network 400 if the color of the manufacturedproduct/item matches or is within the predetermined threshold 2520. Inthe hypothetical example 2, where the universal color code ofmanufactured product/item is “11ff55,” the server processor 110transmits an accept message to the client device 300 because the colorof the manufactured product/item is within the predetermined threshold2520. That is, the color of the manufactured product/item is acceptedbecause it is very similar to the color of the ordered product/item.However, the server processor 110 transmits a reject massage to theclient device 300 over the communications network if the manufacturedproduct/item does not match or is not within the predetermined threshold2520. In the hypothetical example 1, where the universal color code ofmanufactured product/item is “11ffcc,” the server processor 110transmits a reject message to the client device 300 because the color ofthe manufactured product/item is not within the predetermined threshold2520. That is, the color of the manufactured product/item is rejectedbecause it is different from the color of the ordered product/item.

For an unauthorized Merchant user or non-licensee of the serviceprovider, when the client device 300 associated with the unauthorizedMerchant user (i.e., non-subscriber) attempts to access the server 100,in accordance with an exemplary embodiment of the claimed invention, theserver processor 110 denies the client device 300 access to the server100 and transmits a registration webpage to the client device 300 so theuser can subscribe to the services provided by the service provider andbecome a registered/authenticated subscriber using any known methods.After completing the registration process, the user has an option ofdownloading the mobile normalization and/or categorization processapplication onto her client device 300 to perform normalization,codification and categorization of the digital images 2500 locally onher client device 300. In addition or alternatively, the server 100 maypermit the client device 300 of the unauthorized Merchant user totransmit digital image or data associated with the ordered product/itemto the server 100 for normalization, codification and categorization. Asexemplary shown in FIG. 12, the image processor 180 performs eithermobile or full normalization process 2630 on both the digital image 2510of the manufactured product/item and the image/data of the orderedproduct/item received from the client device 300 to identify theuniversal color code(s), preferably, the color hexadecimal code(s), ofthe of the manufactured product/item and ordered product/item. It isappreciated that the image/data of the ordered product/item may be fromthe Merchant's IMS 500 or SCM system 510. The server processor 110 thencompares/analyzes the universal color codes of the manufacturedproduct/item and ordered product/item to determine if the color of themanufactured product/item matches or is within predetermined thresholdof the color of the ordered product/item, similar to the process for theauthorized Merchant users.

The only way to correct inventory problems with the products are whilethey are in the SCM system 510, i.e., before the product is fullyproduced/manufactured. Those changes depend on the particularmanufacturing stage of the product. Once the product is manufactured andenters the IMS 500, it is generally too late to make any substantivechanges to the product. For instance, take a tee shirt. Once the rawfabric is converted and dyed into colors, the only change that can bemade to the tee shirt is to change its style. For example, a crew neckcan be substituted with a V-Neck or a short sleeve can be converted to along sleeve. The earlier a mistake is identified and corrected in theproduction process, the more flexibility a manufacturer has to correctthe mistake. The claimed color based and product related categorizationin the SCM system 510 provides the necessary tool to implement thischange in real-time and/or through predictive analytics.

The only way to correct inventory once it is part of the IMS 500 is toeither reduce the price, return it to the supplier/manufacturer/vendor,or not ship it from the country of manufacturing origin to save duty andshipping costs. This is far less efficient/cost effective thanidentifying and correcting the problem while the product is part of theSCM system 510.

Generally, a formatted Spec Sheet allows the data to be conveyed fromdesign to the SCM system 510 of the factory and the relevant componentsuppliers. In turn, the factory compiles all of the product-relatedinformation to provide cost sheets, minimums, and other relevant data inreal-time to the Merchants.

Product data management (PDM) is the business function often withinproduct lifecycle management (PLM) that is responsible for themanagement and publication of product data. The product data managementis the only way to ensure that everyone is on the same page and thatthere is no confusion during the execution of the processes and that thehighest standards of quality controls are maintained.

Product data management is the use of software or other tools to trackand control data related to a particular product. The data trackedusually involves the technical specifications of the product,specifications for manufacture and development, and the types ofmaterials that will be required to produce goods. The use of productdata management allows a company to track the various costs associatedwith the creation and launch of a product. Product data management ispart of product lifecycle management and configuration management.

Within PDM, the focus is on managing and tracking the creation, changeand archive of all information related to a product. The informationbeing stored and managed (on one or more file servers) will includeengineering data such as computer-aided design (CAD) models, drawingsand their associated documents.

Product data management (PDM) serves as a central knowledge repositoryfor process and product history, and promotes integration and dataexchange among all business users who interact with products, includingproject managers, engineers, sales people, buyers, and quality assuranceteams.

The central database will also manage metadata such as owner of a fileand release status of the components. The package will: control check-inand check-out of the product data to multi-user; carry out engineeringchange management and release control on all versions/issues ofcomponents in a product; build and manipulate the product structure billof materials (BOM) for assemblies; and assist in configurationsmanagement of product variants.

This enables automatic reports on product costs, etc. Furthermore, PDMenables companies producing complex products to spread product data intothe entire PLM launch-process. This significantly enhances theeffectiveness of the launch process.

Product data management is focused on capturing and maintaininginformation on products and/or services through its development anduseful life. Typical information managed in the PDM system 2000 includebut not limited to: part number, part description, supplier/vendor,vendor part number and description, unit of measure, cost/price,schematic or CAD drawing, and material data sheets.

Utilities and advantages of PDM include: track and manage all changes toproduct related data; spend less time organizing and tracking designdata; improve productivity through reuse of product design data; enhancecollaboration; and helps using visual management

PDM stems from traditional engineering design activities that createdproduct drawings and schematics on paper and using CAD tools to createparts lists (Bills of Material structures—BOM). The PDM and BOM data isused in enterprise resource planning (ERP) systems to plan andcoordinate all transactional operations of a company (sales ordermanagement, purchasing, cost accounting, logistics, etc.)

PDM is a subset of a larger concept of product lifecycle management(PLM). PLM encompasses the processes needed to launch new products(NPI), manage changes to existing products (ECN/ECO) and retire productsat the end of their life (End of Life).

PDM system 2000 is the bridge between the SCM system 510 and the IMS500. In accordance with an exemplary embodiment of the claimedinvention, the claimed system is a universal digital color language orsystem to categorize the color-based, product-related, andconsumer-centric data. Without a common denominator, e.g., color, thereis no meaningful way to organize all of this data—which is why “BIGDATA” has failed so far.

In accordance with an exemplary embodiment of the claimed invention, asexemplary shown in FIGS. 21 and 22, the claimed system categorizes thesearch results by color and by product category and as part of itsprocess of normalizing, codifying and categorizing IMS feeds 505 and 515to reverse map and convert Merchants' divergent color systems into oneuniversal color language/system. That is, the middleware engine 520receives product data from the product data management systems 2000 of aplurality of Merchants at step 2010. The middleware engine formats,normalizes, codifies and categorizes the product data into one universalcolor language/system at step 2020. The middleware engine 520 stores theformatted, normalized, codified and categorized SCM data 515 into theappropriate Merchant's SCM system 510, preferably the Merchant's SCMdatabase (shown as the part of the SCM system 510) at step 2030. Themiddleware engine 520 stores the formatted, normalized, codified andcategorized IMS data 505 into the appropriate Merchant's IMS 500,preferably the Merchant's IMS database (shown as the part of the IMS500) at step 2040. In accordance with an exemplary embodiment of theclaimed invention, the color search engine 120 of the server 100provides the verified user access to the search query functions via agraphical user interface (GUI) 700 and the processor 110 of the server100 provides the verified Merchant user with access to additional dataavailable to them under its subscription. Unlike the consumeruser/subscriber, the Merchant user/subscriber can search the SCM systems510 to determine the production status/schedule of a particular productand/or to examine/verify the color and specification of the componentsof the product before moving forward with the production of the product.

As described herein, the color search engine 120 searches the databaseengine 250 that meet the user's color search criteria 2400, e.g., theassociated digital color code(s) corresponding to the selected colorswatch(es) 702, at step 2050. The color search engine 120 transmits thesearch results 2420 containing information about the products matchingthe user's color search criteria 2400 to the client device 300associated with the user over the communications network at step 2060.The color search engine 120 stores the color search criteria 2400 andthe search results 2420 in the data warehouse 200. Preferably, the colorsearch engine 120 updates the user color preference history 2430 basedon the user's color search criteria 2400.

As described herein, the product categorization engine 190 categorizesthe search results based on color and product category at step 2070. Asexemplary shown in FIGS. 19-22, the product categorization engine 190 ofthe server 100 determines the product category of the color analyzedproduct, e.g., clothing, furniture, car, etc., and categorizes the coloranalyzed product by product category at step 565. The productcategorization engine 190 stores the categorized search results in thepersonalized database 209 at step 2080. That is, the productcategorization engine 190 stores categorized search results includingthe personalized information, such as user name, store name, brand name,age, gender, etc., or personalized search results in the personalizeddatabase 209. The middleware engine 520 strips personalized information,such as any information that can identify the Merchant and user whoinitiated the query from the categorized search results to providedepersonalized search results at step 2090. The middleware engine 520stores the depersonalized search results in the depersonalized database210 at step 2100. In other words, the color search engine 120 andproduct categorization engine 190 conveys the user's selections orrecords to the real-time analytics processor 170 of the server 100 forprocessing and analysis.

In accordance with an exemplary embodiment of the claimed invention, thereal-time analytics processor 170 can access the depersonalized database210 to analyze the data for trends and preferences at step 2120. Also,the real-time analytics processor 170 can analyze the depersonalizeddata at step 590 to determine a common or typical profile of userspurchasing such a product or to determine color trends based on gender,age, geo-location and the like. Such data analytics would be useful toMerchants for both marketing and operations purposes.

In accordance with an exemplary embodiment of the claimed invention, thereal-time analytics processor 170 can access the personalized database209 at step 2130 to determine user preferences for colors and patternsby analyzing user browsing and purchasing behavior, and with associateduser data, such as demographic data. Such information can be madeavailable across a variety of user variables (e.g., gender, age,geography, etc.). Also, at step 590, the real-time analytics processor170 can couple the demographic data with other data such as, but notlimited to, a user's purchase and shopping history, as well as dataregarding industry trends and consumer color preferences, so as toalgorithmically recommend colors and products to both users andMerchants.

In accordance with an exemplary embodiment of the claimed invention, themiddleware engine 520 re-categorizes the formatted, normalized, codifiedand categorized IMS data 505 in the Merchant's IMS 500, preferably theMerchant's IMS database, in accordance with the categorized searchresult, preferably de-personalized categorized search result. Also, themiddleware engine 520 re-categorizes the formatted, normalized, codifiedand categorized SCM data 515 in the Merchant's SCM system 510,preferably the Merchant's SCM database, in accordance with thecategorized search result, preferably de-personalized categorized searchresult.

In accordance with an exemplary embodiment of the claimed invention, themiddleware engine 520 utilizes the users' browsing histories and/orcolor preference histories to re-categorize the categorized IMS data 505and the categorized SCM data 515. Preferably, the middleware engine 520weights various information in the users' color preference historiesand/or browsing histories differently, such as based on the relevancy ofthe information by giving a greater weight the purchased products/itemsthan viewed products/items.

In accordance with an exemplary embodiment of the claimed invention, asexemplary shown in FIG. 23, the claimed system normalizes the physicalimage 380, e.g., a digital image 380 of the color swatch 390, capturedby a camera 310, preferably RGB camera, of the client device 300. Thedigital image 380 can be captured using the light source 370 to providespectral adjustments of the lighting conditions to standardize the RGBreadings from different client devices 300. The processor 320 of theclient device 300 converts the captured digital image into a RGB colorimage of the color swatch 390 in step 3000. The processor 320 normalizesthe RGB colors of the color swatch in step 3010. In step 3010, theprocessor 320 segments the RGB color image of the color swatch 390 intoa plurality of segments and analyzes each segment to determine adominant color for each segment. Additionally, in step 3010, theprocessor 320 determines at least one dominant color for the colorswatch 390 based on prevalence of said at least one dominant color ineach segment. Further, in step 3010, the processor 320 assigns ahexadecimal code of the universal color system to the color swatch 390that is closest to a digital hexadecimal value of the RGB image of thecolor swatch 390 based on color component intensity values of at leastone dominant color of the color swatch 390, thereby normalizing RGBcolors of the color swatch 390. The processor 320 obtains thehexadecimal code of the universal color system from the universal colordatabase 208. The processor 320 stores the digital image 380 of thecolor swatch 390, the RGB image of the color swatch 390, at least onedominant color for color swatch 390, and the hexadecimal code assignedto the color swatch 390 to the data warehouse 200. Preferably, thehexadecimal code assigned to the color swatch 390 is stored in a memory330 or the universal color swatch internal database 209.

In accordance with an exemplary embodiment of the claimed invention, asexemplary shown in FIG. 24, the claimed system normalizes the physicalimage 380, e.g., a digital image 380 of the color swatch 390, capturedby a camera 310, preferably RGB camera, of the client device 300, andcompares the normalized image of the color swatch 390 to the standardcolor swatches stored in the universal color swatch internal database209. The digital image 380 can be captured using the light source 370 toprovide spectral adjustments of the lighting conditions to standardizethe RGB readings from different client devices 300. The processor 320 ofthe client device 300 converts the captured digital image into a RGBcolor image of the color swatch 390 in step 3000. The processor 320normalizes the RGB colors of the color swatch in step 3010. In step3010, the processor 320 segments the RGB color image of the color swatch390 into a plurality of segments and analyzes each segment to determinea dominant color for each segment. Additionally, in step 3010, theprocessor 320 determines at least one dominant color for the colorswatch 390 based on prevalence of said at least one dominant color ineach segment. Further, in step 3020, the processor 320 assigns ahexadecimal code of the universal color system to the color swatch 390that is closest to a digital hexadecimal value of the RGB image of thecolor swatch 390 based on color component intensity values of at leastone dominant color of the color swatch 390, thereby normalizing RGBcolors of the color swatch 390. The processor 320 obtains thehexadecimal code of the universal color system from the universal colordatabase 208.

In accordance with an exemplary embodiment of the claimed invention, theprocessor 320 determines whether the hexadecimal code assigned to thecolor swatch 390 matches a hexadecimal code of one of standard colorswatches in step 3030. The processor 320 retrieves the standard colorswatches from the universal color swatch internal database 209 or frommemory 330. The processor 320 accepts the color swatch 390 in responseto a determination that the hexadecimal code assigned to the colorswatch matches the hexadecimal code of one of the standard colorswatches in step 3050. The processor 320 rejects the color swatch 390 inresponse to a determination that the hexadecimal code assigned to thecolor swatch does not match the hexadecimal code of any of the standardcolor swatches in step 3050. In accordance with an aspect of the claimedinvention, the network connection facility 350 of the client device 300transmits an acceptance message to another client device 300 over acommunications network 400 upon acceptance of the color swatch 390. Thenetwork connection facility 350 of the client device 300 transmits arejection message of the color swatch 390 to another client device 300over the communications network upon rejection of the color swatch 390.

In accordance with an exemplary embodiment of the claimed invention, thecolor tolerances or range is preset or predetermined at step 3060. Theprocessor 320 determines whether the hexadecimal code assigned to thecolor swatch 390 is within a predetermined range of a hexadecimal codeof one of standard color swatches in step 3050. The processor 320accepts the color swatch 390 in response to a determination that thehexadecimal code assigned to the color swatch 390 is within thepredetermined range in step 3050. The processor 320 rejects the colorswatch 390 in response to a determination that the hexadecimal codeassigned to the color swatch 390 is not within the predetermined rangein step 3050.

All color data is displayed with RGB, the native language for allmonitors worldwide. Web crawlers can extract the color data in RGB orhexadecimal from an image or a swatch but the web crawlers cannotinterpret the data due to the massive amount of duplication in the16,777,216 mapped color coordinates that represent the digital colorspace. Thousands of coordinates that represent a color are simply notany more discernible to a web crawler than the human eye and, as aresult, the redundant data cannot be parsed, categorized, or interpretedin a useful manner.

Using the same method and system for web crawlers, as is used in the SCMor IMS systems, as described herein, the RGB or HEX color data can benormalized into a universal color standard. It is important to note thatnormalizing the RGB color space does not eliminate any of the mappedcoordinates, but rather consolidates the duplication into a standardizedcolor language. In accordance with an exemplary embodiment of theclaimed invention, the normalized color data collected by a web crawlernow allows the web crawler and attached analytics systems to parse,categorize and interpret the data to provide valuable insights intoconsumer behavior.

Yet another drawback with the color display for images and swatches onthe eCommerce platform is that there is currently no reliable method tomatch an image to a physical product. This is currently done by eye. Asno two people see or describe color the same way, this method leads tocolor discrepancy between the physical product and the digital image.This presents a problem for online shoppers as they must rely on thecolor represented by digital image when they shop for product online.This problem makes it impossible to color coordinate multiple items whenshopping online, which is why most traditional retailers prefer fortheir customers to shop at the physical store. Typically, in a physicalstore, there is sales help that can help customers to color coordinatethe physical product and there is no issue with the colormisrepresentation in an image.

The solution to matching a physical product to a digital image is tocreate a digital standard that can be compared to the digital imageprogrammatically instead of doing the comparison with the human eye. Inaccordance with an exemplary embodiment of the claimed invention, ahomogenized eCommerce platform is provided. The standard can be createdat design inception or, more preferably, after the final product iscompleted. Using a spectrometer, the photographer can extract the RGB orhexadecimal value from the physical product and then normalize it into adigital standard. This allows the photographer to use a computerapplication to process the color standard to the color in the image andcompare the two by measuring the delta E. Once the digital image matchesthe product, the photographer can embed the metadata into the image. Inaccordance with an exemplary embodiment of the claimed invention, themetadata comprises product information, including but not limited to,the internal color name, internal color barcode number, and thenormalized universal digital reference mapping standard. The claimedinvention enables the eCommerce platform to programmatically homogenizeall color descriptive and data across all brands on the eCommerceplatform, platform to platform. Once the color data is homogenizedacross all brands and product on the eCommerce platform in accordancewith an embodiment of the claimed invention, the ability to colorcoordinate those products become possible.

In accordance with an exemplary embodiment of the claimed invention, acomputer-implemented method for normalizing the RGB digital color spaceinto a universal digital color standard is provided. The RGB digitalcolor space is mapped into a three-dimensional color cube. The sides ofthe three-dimensional color cube get progressively smaller until thesides converge in a center point of the three-dimensional color cube toform a three-dimensional color nesting cube. Duplicate colors in the RGBdigital color space that are not distinguishable to a human eye areconsolidated to obtain a normalized color space. The normalized colorspace is organized into swatch buckets to obtain a normalizedthree-dimensional color nesting cube. Each cube of the normalizedthree-dimensional color nesting cube represents a unique mapping code ofthe universal digital color standard.

In accordance with an exemplary embodiment, a user can search for aproduct by color even though it is an attribute that cannot be describedadequately using words or numbers that represent digital colorcoordinates that are not distinguishable to the human eye. Additionally,in accordance with an exemplary embodiment of the claimed invention, adata base can collect and analyze color data that is displayed in RGBand coded in hexadecimal.

The proximity of color coordinates that make up the RGB color space, thenative language for all monitors, makes it difficult to properly search,display or collect data about or distinguish the attributes of a coloron an eCommerce platform. For example, the color “red” can be describedby thousands of digital color coordinates that are not discernable tothe human eye or a machine. FF2704, FF1F00, FE2000, FE2001, R:255 G:39B:4, R:254 G:31 B:0, R:254 G:32 B:0, R:254 G:32 B:1, and thousands ofothers that make up a portion of the 16,777,216 coordinates that map adigital space are not distinguishable by the human eye or a machine fora particular shade of the red family of colors. The numbers themselvesdo not readily convey meaning. In this sense, the digital color numberscan create the same type of “color chaos” as subjective and meaninglesscolor descriptive. This makes it difficult to collect, parse, andinterpret color and other product data. It also adds to the problem ofmatching physical products to digital images that create a chaoticshopping platform. Further, this all contributes to the inability toengage machine learning to color coordinate products, patterns, andobjects to increases sales and service on an eCommerce platform.

To further separate digital color coordinates that would be morediscernable to the human eye, a new simplified mapping system isprovided in accordance with an exemplary embodiment of the claimedinvention. The solution starts by consolidating the millions ofduplicate colors in the RGB color space to a normalized color space, thenative language for all monitors, that are not distinguishable to thehuman eye. The normalized color space is then organized into swatchbuckets to create a universal digital color standard. This uniquemapping system of the claimed invention has the ability to translate andhomogenize all of chaotic color descriptions and digital coordinatesinto a defined color language and defined data points. As machinelearning heavily relies on data samples. The more data points that acomputer program, machine or computer can sample and define, the better.Integrating the universal digital color language into all existing colorsystems not only makes data trackable, the universal digital colorlanguage of the claimed invention also makes it teachable to a computer.In accordance with an exemplary embodiment of the claimed invention, theuniversal digital color langue enables an Artificial Intelligenceprogram to integrate with the homogenized eCommerce platform, whetherthrough the IMS, SCM, or a web crawler to provide personalizedsuggestions to color coordinate product selections for online shoppers.

To accomplish this, as shown in FIG. 25, in accordance with an exemplaryembodiment of the claimed invention, the RGB digital color space forms athree-dimensional color cube 4000 with eight corners, six sides and adistinct point in the center of grayscale, in the middle of the blackand white corners. The two corners being black and white, the other sixcorners being red, yellow, green, cyan, blue and magenta. The color cubecan be normalized into a standard. The normalized color cube 4000 can bedivided into sides and layers just like a Russian nesting doll. Thethree-dimensional normalized color cube 4000 is converted into twodimensional slices that map all of the sides and layers as one movesmove from the outside of the cube to the center point. That is, thethree-dimensional cube 4000 is a normalized digital color nesting cube4000.

As shown in FIG. 25, each of the six sides of the nesting cube 4000 getsprogressively smaller as one approaches the center point of the nestingcube 4000. Adding a grid to divide each unique side of the nesting cube,which changes layer to layer, provides the basis to map the grid usinglongitude and latitude. In accordance with an exemplary embodiment ofthe claimed invention, the grid creates a mapping system based on theHue Axis Corner, Longitude, Latitude, and Saturation Layer. As exemplaryshown in FIGS. 26A-29B, the grid can be navigated by Hue Axis Corner,Longitude, Latitude, and Layer. The grid is comprised of normalized“swatch buckets” that contain all of the coordinates in a digital colorspace. After consolidating the redundancy, the normalized color spacecan be normalized and organized into smaller color buckets that arediscernable to the human eye.

Print systems do not properly convert to digital systems. One problem isthat print swatch books only cover 2500-3500 colors, far less than the16,777,216 coordinates that comprise a 24-bit digital color space.Another problem is that print systems only cover about 40% of the gamutin the digital space. Still another problem is that, unlike all digitalsystem which are perfectly symmetrical, print systems are asymmetrical.As a result of the issues, print systems do not have the gamut orstructure to normalize a digital color space or to display swatches inan organized manner. A normalized color nesting cube 4000 of the claimedinvention resolves all issues for display, mapping, and communication.

As shown in FIG. 25, RGB and HEX form a normalized digital color nestingcube 4000 that can be graphed to 255+1 on the outside, 127+1 saturationto the center point (R:128, G:128, B: 128). The normalized cube 4000consolidates the duplication to 30+1 on the outside layer, 15+1saturation to the center point. Both the un-normalized digital cube andthe normalized cube are laid out as perfectly symmetrical systems.Failure to maintain symmetry collapses the cube structure.

Without normalization, no current digital numbering systems isdiscernable to the human eye or teachable to a machine, which reliesheavily on data samples. The more data points you can sample and define,the better. A normalized universal digital color language not only makesdata trackable but makes it teachable to a computer. Teaching a machine,the color language would enable the machine to learn how tocolor-coordinate products, objects, and patterns. This would provideeCommerce platforms with the ability to personalize color preferences tohelp customers to color-coordinate products while shopping online,providing a sales tool that is currently not possible or available. Auniversal standard would also create the ability to “homogenize” all ofthe color inputs (digital coordinates like HEX and RGB) and colordescriptive across all diverse brands on the eCommerce platform. Thiswould make it far easier to replicate the shopping experience on atraditional retail floor.

As shown in FIG. 26A, the Hue Axis Corner (Red Yellow Green Cyan BlueMagento) appears on the top left corner of the icon that represents oneof the six sides of the cube 4000. As exemplary shown in FIGS. 26B-C,the Hue Axis Corner runs diagonally to the bottom right corner, whichrepresents a grayscale. As exemplary shown in FIG. 26B-c, the hue valueincreases by 60° when moving across the grid to the right (longitude)and decreases 60° when moving down toward the bottom left corner(latitude). The same hue value applies to the side, regardless of thelayer.

As exemplary shown in FIGS. 27A-C, all of the lettered layers are basedon the saturation or intensity of a color. Layer A, which appears on theoutside of the normalized mapping cube 4000 is the most saturated. Asexemplary shown for a red side (FIG. 27B) and a yellow side (FIG. 27C)of the normalized mapping cube 4000, each pursuant layer becomes lesssaturated until all layers converge at the center point (Layer X) of thenormalized mapping cube 4000. While the grid and size of the side isreduced as the layers approach Layer X, the positioning of the Hue AxisCorners always remain the same.

As exemplary shown in FIG. 28, the individual swatch buckets for eachHue Axis Corner are divided into a mapping grid. As the layers move fromthe outside of the normalized nesting cube (Layer A) to the center(Layer X) the swatch bucket grids get larger. For example, the size ofthe mapping grid on the outside, Layer A, is 31×31, Layer G is 19×19,Layer Q is 3×3. In accordance with an exemplary embodiment of theclaimed invention, the claimed mapping grids are navigated by Longitudeand Latitude.

In accordance with an exemplary embodiment of the claim invention, asexemplary shown in FIGS. 29A-B, the six-digit color mapping code isbased on the Axis Hue Corner (one digit), Longitude (two digits),Latitude (two digits), and Layer (one digit). The claimed color mappingcode that represents the mapping of the normalized cube 4000 is simpleto teach and even simpler to learn, far more so than all other digitalcodes. Unlike other codes or coordinates, the color mapping code of theclaimed mapping system can convert the color without the need to see thecolor swatch. As exemplary shown in FIG. 29A, R0400A represents a colorswatch bucket that starts at the Red Hue Axis Corner, moves fourswatches to the right (Longitude), zero swatches down (Latitude), and ison the outside of the cube on the “A” Saturation Layer. As exemplaryshown in FIG. 29B, Y0402N represents a color swatch bucket that startsat the Yellow Hue Axis Corner, moves four swatches to the right(Longitude), two swatches down (Latitude), and is on the inner part ofthe cube on the “N” Saturation Layer.

Digital coordinates are difficult for the average person to understandand convey no meaning without a swatch to help identify a color. Thecolor mapping code that defines the normalized nesting cube 4000 doesjust the opposite. As exemplary shown in FIGS. 30A-C, the color mappingcode of the claimed mapping system makes it possible to identify acolor, with or without the help of a swatch, making it possible to teachto someone that is color blind or to a machine. Teaching a colorlanguage to a machine is the first step to teaching a machine how tocolor coordinate products, patterns, and objects to provide conciergesales help on an eCommerce platform. The claimed invention providessales and services to online shoppers that are currently impossible toachieve.

In accordance with an exemplary embodiment of the claimed invention,FIG. 31 is an exemplary flow chart depicting a process for color mappingand machine learning to color coordinate products, patterns and objectson a homogenized eCommerce platform in accordance with an exemplaryembodiment of the claimed invention. For simplicity, an exemplaryprocess for machining learning to color coordinate products on ahomogenized eCommerce platform will be described herein, but the processis equally applicable to machining learning to color coordinate patternsand objects. At step 4100, the server processor 110 or the clientprocessor 320 generates a color standard for physical product using theprocess and methodology already described herein, the discussion willnot be repeated here, and exemplary shown in FIGS. 3A-B, 5, 7 and 19-20.At step 4110, the camera 310, preferably RGB camera, of the clientdevice 300 captures the digital image of the physical product. At step4120, the server processor 110 or the client processor 320 matches thedigital image of the physical product to the color standard for thephysical product using the process and methodology already describedherein, the discussion will not be repeated here, and exemplary shown inFIGS. 23-24.

The server processor 110 or the client processor 320 embeds metadataincluding the color standard into the digital image at step 4130 anduploads the metadata embedded digital image to eCommerce platform atstep 4140. In accordance with an exemplary embodiment of the claimedinvention, the metadata comprises product information, including but notlimited to, the internal color name, internal color barcode number, andthe normalized universal digital color mapping standard.

At step 4150, the server processor 110 or eCommerce platform processorhomogenizes the color data of plurality of products across the eCommerceplatform to color coordinate products using a single universal digitalcolor mapping standard accordance with an exemplary embodiment of theclaimed invention.

At steps 4160 and 4170, the user, i.e., an online shopper, is shown agraphical user interface as exemplary shown in FIG. 14 with a normalizedcolor palette or color bar display 2610 or 2620 to locate the desiredproduct. The process of searching a product by normalized color paletteof the universal digital color standard has already described herein,the discussion will not be repeated here, and as exemplary shown inFIGS. 15-17.

At step 4180, artificial Intelligence program integrated with thehomogenized eCommerce platform, whether through the IMS, SCM, or a webcrawler to provide personalized suggestions to color coordinate productselections for online shoppers. As already discussed herein, thepersonalized suggestions can be based on analytics relating to userpreferences for colors and patterns by analyzing user browsing andpurchasing behavior, word association, color selections and withassociated user data, such as demographic data. Such information can bemade available across a variety of user variables (e.g., gender, age,geography, etc.).

In accordance with an exemplary embodiment of the claimed invention, amapping system for machine learning to color coordinate products,patterns and objects on a homogenized eCommerce platform implementingthe method for normalizing the RGB digital color space into theuniversal digital color standard is provided. Each client device 300 isuniquely associated with an online shopper. The database engine 200comprises a plurality of products available on the homogenized eCommerceplatform. The processor-based server 100 of the eCommerce platformconnected to a communication system receives search queries from aplurality of client devices. The database engine 200 is searched forproducts matching the search queries. The products matching the searchqueries and color coordinated product suggestions generated based on thesearch queries are displayed on the respective client devices 300.

In accordance with an exemplary embodiment of the claimed invention, theprocessor-executable or computer-executable instructions may be storedon a computer-readable medium, such as a CD, DVD, flash memory, or thelike. The processor-executable or computer-executable instructions mayalso be stored as a set of downloadable processor-executable orcomputer-executable instructions, for example, or downloading andinstalling from an Internet location (e.g., Web server).

The accompanying description and drawings only illustrate severalembodiments of a system, methods and interfaces for color-basedidentification, searching and matching, however, other forms andembodiments are possible. Accordingly, the description and drawings arenot intended to be limiting in that regard. Thus, although thedescription above and accompanying drawings contain much specificity,the details provided should not be construed as limiting the scope ofthe embodiments but merely as providing illustrations of some of thepresently preferred embodiments. The drawings and the description arenot to be taken as restrictive on the scope of the embodiments and areunderstood as broad and general teachings in accordance with the presentinvention. While the present embodiments of the invention have beendescribed using specific terms, such description is for presentillustrative purposes only, and it is to be understood thatmodifications and variations to such embodiments may be practiced bythose of ordinary skill in the art without departing from the spirit andscope of the invention.

1. A computer-implemented method for normalizing a RGB (red, green,blue) digital color space into a universal digital color standard,comprising: mapping the RGB digital color space into a three-dimensionalcolor cube, sides of the three-dimensional color cube get progressivelysmaller until the sides converge in a center point of thethree-dimensional color cube to form a three-dimensional color nestingcube; consolidating duplicate colors in the RGB digital color space thatare not distinguishable to a human eye to obtain a normalized colorspace; and organizing the normalized color space into swatch buckets toobtain a normalized three-dimensional color nesting cube, each cube ofthe normalized three-dimensional color nesting cube representing aunique mapping code of the universal digital color standard.
 2. Themethod of claim 1, wherein the normalized three-dimensional colornesting cube has a red side with a red hue axis corner, a yellow sidewith a yellow hue axis corner, a green side with a green hue axiscorner, a cyan side with a cyan hue axis corner, a blue side with a bluehue axis corner, and a magneto side with a magneto hue axis corner. 3.The method of claim 2, further comprising slicing the normalizedthree-dimensional color nesting cube into connecting two-dimensionalslices, each two-dimensional slice forming a grid mapping the normalizedthree-dimensional color nesting cube to a hue axis corner, a longituderepresenting a horizontal movement within the grid, a latituderepresenting a vertical movement within the grid and a layerrepresenting a saturation or intensity of a color.
 4. The method ofclaim 3, wherein the unique mapping code is defined by the hue axiscorner, the longitude, the latitude and the layer.
 5. The method ofclaim 4, further comprising matching a digital image of a product to theunique mapping code by: segmenting the digital image into a plurality ofsegments; analyzing each segment to determine a dominant color for saideach segment; determining at least one dominant color based onprevalence of said at least one dominant color in said each segment; andassigning the unique mapping code of the universal digital colorstandard to the product that is closest to a cube of the normalizedthree-dimensional color nesting cube based on color component intensityvalues of said at least one dominant color of the product.
 6. The methodof claim 5, further comprising embedding metadata comprising the uniquemapping code to the digital image of the product and uploading thedigital image embedded with the metadata to an eCommerce platform. 7.The method of claim 6, further comprising homogenizing color data acrossthe eCommerce platform to provide a homogenized eCommerce platform by:matching a digital image of each product offered in the eCommerceplatform to the unique matching code of the universal digital colorstandard; embedding the metadata to the digital image of said eachproduct; and uploading the digital image of said each product embeddedwith the metadata to the eCommerce platform.
 8. The method of claim 7,further comprising displaying a graphical user interface with anormalized color palette of the universal digital color standard to anonline shopper on the homogenized eCommerce platform so the onlineshopper can search for a desired product by the normalized color paletteof the universal digital color standard.
 9. The method of claim 8,further comprising artificial intelligence and machine learning theuniversal digital color standard to color coordinate products on thehomogenized eCommerce platform; and generating color coordinated productsuggestions based on the mapping code of the desired product.
 10. Amapping system for machine learning to color coordinate products,patterns and objects on a homogenized eCommerce platform implementingthe method for normalizing the RGB digital color space into theuniversal digital color standard of claim 9, comprising: a plurality ofprocessor-based client devices, each client device uniquely associatedwith an online shopper; a database engine comprising a plurality ofproducts available on the homogenized eCommerce platform; and aprocessor-based server of the eCommerce platform connected to acommunication system to receive search queries from a plurality ofclient devices; search the database engine for products matching thesearch queries; display the products matching the search queries andcolor coordinated product suggestions generated based on the searchqueries.